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+
    
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    </pre>
    
 
    
 
    
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    end{sphinxVerbatim}
    
 
    
 
    
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    pred_probs.npz      100%[===================>]  16.26M  89.6MB/s    in 0.2s
    
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    [3]:
diff --git a/master/tutorials/token_classification.ipynb b/master/tutorials/token_classification.ipynb
index 9b2f4aa01..e96e1caaf 100644
--- a/master/tutorials/token_classification.ipynb
+++ b/master/tutorials/token_classification.ipynb
@@ -75,10 +75,10 @@
    "id": "ae8a08e0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:04.174708Z",
-     "iopub.status.busy": "2024-02-13T00:43:04.174530Z",
-     "iopub.status.idle": "2024-02-13T00:43:05.448184Z",
-     "shell.execute_reply": "2024-02-13T00:43:05.447435Z"
+     "iopub.execute_input": "2024-02-13T01:08:50.680983Z",
+     "iopub.status.busy": "2024-02-13T01:08:50.680568Z",
+     "iopub.status.idle": "2024-02-13T01:08:52.047522Z",
+     "shell.execute_reply": "2024-02-13T01:08:52.046779Z"
     }
    },
    "outputs": [
@@ -86,7 +86,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "--2024-02-13 00:43:04--  https://data.deepai.org/conll2003.zip\r\n",
+      "--2024-02-13 01:08:50--  https://data.deepai.org/conll2003.zip\r\n",
       "Resolving data.deepai.org (data.deepai.org)... "
      ]
     },
@@ -94,16 +94,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "169.150.236.97, 2400:52e0:1a00::1070:1\r\n",
-      "Connecting to data.deepai.org (data.deepai.org)|169.150.236.97|:443... connected.\r\n",
-      "HTTP request sent, awaiting response... "
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "200 OK\r\n",
+      "185.93.1.246, 2400:52e0:1a00::1069:1\r\n",
+      "Connecting to data.deepai.org (data.deepai.org)|185.93.1.246|:443... connected.\r\n",
+      "HTTP request sent, awaiting response... 200 OK\r\n",
       "Length: 982975 (960K) [application/zip]\r\n",
       "Saving to: ‘conll2003.zip’\r\n",
       "\r\n",
@@ -116,9 +109,9 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "conll2003.zip       100%[===================>] 959.94K  4.82MB/s    in 0.2s    \r\n",
+      "conll2003.zip       100%[===================>] 959.94K  --.-KB/s    in 0.1s    \r\n",
       "\r\n",
-      "2024-02-13 00:43:04 (4.82 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n",
+      "2024-02-13 01:08:51 (7.92 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n",
       "\r\n",
       "mkdir: cannot create directory ‘data’: File exists\r\n"
      ]
@@ -138,9 +131,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "--2024-02-13 00:43:05--  https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n",
-      "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 52.217.140.217, 52.217.108.172, 52.217.124.193, ...\r\n",
-      "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|52.217.140.217|:443... connected.\r\n",
+      "--2024-02-13 01:08:51--  https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n",
+      "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 52.217.82.132, 54.231.138.209, 3.5.28.120, ...\r\n",
+      "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|52.217.82.132|:443... connected.\r\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "HTTP request sent, awaiting response... "
      ]
     },
@@ -161,9 +160,17 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "pred_probs.npz      100%[===================>]  16.26M  89.6MB/s    in 0.2s    \r\n",
+      "pred_probs.npz       44%[=======>            ]   7.25M  36.3MB/s               "
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "pred_probs.npz      100%[===================>]  16.26M  60.7MB/s    in 0.3s    \r\n",
       "\r\n",
-      "2024-02-13 00:43:05 (89.6 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n",
+      "2024-02-13 01:08:51 (60.7 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n",
       "\r\n"
      ]
     }
@@ -180,10 +187,10 @@
    "id": "439b0305",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:05.451079Z",
-     "iopub.status.busy": "2024-02-13T00:43:05.450671Z",
-     "iopub.status.idle": "2024-02-13T00:43:06.564340Z",
-     "shell.execute_reply": "2024-02-13T00:43:06.563771Z"
+     "iopub.execute_input": "2024-02-13T01:08:52.050051Z",
+     "iopub.status.busy": "2024-02-13T01:08:52.049854Z",
+     "iopub.status.idle": "2024-02-13T01:08:53.131521Z",
+     "shell.execute_reply": "2024-02-13T01:08:53.130959Z"
     },
     "nbsphinx": "hidden"
    },
@@ -194,7 +201,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -220,10 +227,10 @@
    "id": "a1349304",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:06.566928Z",
-     "iopub.status.busy": "2024-02-13T00:43:06.566437Z",
-     "iopub.status.idle": "2024-02-13T00:43:06.570020Z",
-     "shell.execute_reply": "2024-02-13T00:43:06.569578Z"
+     "iopub.execute_input": "2024-02-13T01:08:53.134166Z",
+     "iopub.status.busy": "2024-02-13T01:08:53.133673Z",
+     "iopub.status.idle": "2024-02-13T01:08:53.137466Z",
+     "shell.execute_reply": "2024-02-13T01:08:53.137011Z"
     }
    },
    "outputs": [],
@@ -273,10 +280,10 @@
    "id": "ab9d59a0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:06.572045Z",
-     "iopub.status.busy": "2024-02-13T00:43:06.571766Z",
-     "iopub.status.idle": "2024-02-13T00:43:06.574735Z",
-     "shell.execute_reply": "2024-02-13T00:43:06.574279Z"
+     "iopub.execute_input": "2024-02-13T01:08:53.139517Z",
+     "iopub.status.busy": "2024-02-13T01:08:53.139169Z",
+     "iopub.status.idle": "2024-02-13T01:08:53.142016Z",
+     "shell.execute_reply": "2024-02-13T01:08:53.141597Z"
     },
     "nbsphinx": "hidden"
    },
@@ -294,10 +301,10 @@
    "id": "519cb80c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:06.576803Z",
-     "iopub.status.busy": "2024-02-13T00:43:06.576540Z",
-     "iopub.status.idle": "2024-02-13T00:43:15.738283Z",
-     "shell.execute_reply": "2024-02-13T00:43:15.737645Z"
+     "iopub.execute_input": "2024-02-13T01:08:53.143912Z",
+     "iopub.status.busy": "2024-02-13T01:08:53.143722Z",
+     "iopub.status.idle": "2024-02-13T01:09:02.179284Z",
+     "shell.execute_reply": "2024-02-13T01:09:02.178768Z"
     }
    },
    "outputs": [],
@@ -371,10 +378,10 @@
    "id": "202f1526",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:15.740962Z",
-     "iopub.status.busy": "2024-02-13T00:43:15.740620Z",
-     "iopub.status.idle": "2024-02-13T00:43:15.746062Z",
-     "shell.execute_reply": "2024-02-13T00:43:15.745601Z"
+     "iopub.execute_input": "2024-02-13T01:09:02.181744Z",
+     "iopub.status.busy": "2024-02-13T01:09:02.181477Z",
+     "iopub.status.idle": "2024-02-13T01:09:02.186852Z",
+     "shell.execute_reply": "2024-02-13T01:09:02.186427Z"
     },
     "nbsphinx": "hidden"
    },
@@ -414,10 +421,10 @@
    "id": "a4381f03",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:15.748134Z",
-     "iopub.status.busy": "2024-02-13T00:43:15.747800Z",
-     "iopub.status.idle": "2024-02-13T00:43:16.104300Z",
-     "shell.execute_reply": "2024-02-13T00:43:16.103644Z"
+     "iopub.execute_input": "2024-02-13T01:09:02.188840Z",
+     "iopub.status.busy": "2024-02-13T01:09:02.188513Z",
+     "iopub.status.idle": "2024-02-13T01:09:02.542148Z",
+     "shell.execute_reply": "2024-02-13T01:09:02.541571Z"
     }
    },
    "outputs": [],
@@ -454,10 +461,10 @@
    "id": "7842e4a3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:16.106794Z",
-     "iopub.status.busy": "2024-02-13T00:43:16.106584Z",
-     "iopub.status.idle": "2024-02-13T00:43:16.110882Z",
-     "shell.execute_reply": "2024-02-13T00:43:16.110338Z"
+     "iopub.execute_input": "2024-02-13T01:09:02.544756Z",
+     "iopub.status.busy": "2024-02-13T01:09:02.544358Z",
+     "iopub.status.idle": "2024-02-13T01:09:02.548740Z",
+     "shell.execute_reply": "2024-02-13T01:09:02.548281Z"
     }
    },
    "outputs": [
@@ -529,10 +536,10 @@
    "id": "2c2ad9ad",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:16.113016Z",
-     "iopub.status.busy": "2024-02-13T00:43:16.112696Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.488955Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.488232Z"
+     "iopub.execute_input": "2024-02-13T01:09:02.550853Z",
+     "iopub.status.busy": "2024-02-13T01:09:02.550545Z",
+     "iopub.status.idle": "2024-02-13T01:09:04.959158Z",
+     "shell.execute_reply": "2024-02-13T01:09:04.958496Z"
     }
    },
    "outputs": [],
@@ -554,10 +561,10 @@
    "id": "95dc7268",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.492127Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.491369Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.495211Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.494758Z"
+     "iopub.execute_input": "2024-02-13T01:09:04.962283Z",
+     "iopub.status.busy": "2024-02-13T01:09:04.961556Z",
+     "iopub.status.idle": "2024-02-13T01:09:04.965363Z",
+     "shell.execute_reply": "2024-02-13T01:09:04.964836Z"
     }
    },
    "outputs": [
@@ -593,10 +600,10 @@
    "id": "e13de188",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.497244Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.496929Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.502291Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.501828Z"
+     "iopub.execute_input": "2024-02-13T01:09:04.967363Z",
+     "iopub.status.busy": "2024-02-13T01:09:04.967026Z",
+     "iopub.status.idle": "2024-02-13T01:09:04.972235Z",
+     "shell.execute_reply": "2024-02-13T01:09:04.971776Z"
     }
    },
    "outputs": [
@@ -774,10 +781,10 @@
    "id": "e4a006bd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.504313Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.503980Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.529855Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.529371Z"
+     "iopub.execute_input": "2024-02-13T01:09:04.974307Z",
+     "iopub.status.busy": "2024-02-13T01:09:04.973987Z",
+     "iopub.status.idle": "2024-02-13T01:09:05.000776Z",
+     "shell.execute_reply": "2024-02-13T01:09:05.000183Z"
     }
    },
    "outputs": [
@@ -879,10 +886,10 @@
    "id": "c8f4e163",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.531957Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.531643Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.536502Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.535960Z"
+     "iopub.execute_input": "2024-02-13T01:09:05.003014Z",
+     "iopub.status.busy": "2024-02-13T01:09:05.002661Z",
+     "iopub.status.idle": "2024-02-13T01:09:05.007683Z",
+     "shell.execute_reply": "2024-02-13T01:09:05.007189Z"
     }
    },
    "outputs": [
@@ -956,10 +963,10 @@
    "id": "db0b5179",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.538559Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.538225Z",
-     "iopub.status.idle": "2024-02-13T00:43:19.973837Z",
-     "shell.execute_reply": "2024-02-13T00:43:19.973279Z"
+     "iopub.execute_input": "2024-02-13T01:09:05.009826Z",
+     "iopub.status.busy": "2024-02-13T01:09:05.009504Z",
+     "iopub.status.idle": "2024-02-13T01:09:06.463987Z",
+     "shell.execute_reply": "2024-02-13T01:09:06.463485Z"
     }
    },
    "outputs": [
@@ -1131,10 +1138,10 @@
    "id": "a18795eb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:19.976037Z",
-     "iopub.status.busy": "2024-02-13T00:43:19.975689Z",
-     "iopub.status.idle": "2024-02-13T00:43:19.979882Z",
-     "shell.execute_reply": "2024-02-13T00:43:19.979346Z"
+     "iopub.execute_input": "2024-02-13T01:09:06.466176Z",
+     "iopub.status.busy": "2024-02-13T01:09:06.465836Z",
+     "iopub.status.idle": "2024-02-13T01:09:06.469775Z",
+     "shell.execute_reply": "2024-02-13T01:09:06.469321Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/versioning.js b/versioning.js
index 41296d1df..3a012671c 100644
--- a/versioning.js
+++ b/versioning.js
@@ -1,4 +1,4 @@
 var Version = {
   version_number: "v2.5.0",
-  commit_hash: "5408abe9bf41d8c765c17e338a0745474e55460a",
+  commit_hash: "1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8",
 };
\ No newline at end of file

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        "    \n",
        "      \n",
-       "      dark_score\n",
        "      is_dark_issue\n",
+       "      dark_score\n",
        "    \n",
        "  \n",
        "  \n",
        "    \n",
        "      34848\n",
-       "      0.203922\n",
        "      True\n",
+       "      0.203922\n",
        "    \n",
        "    \n",
        "      50270\n",
-       "      0.204588\n",
        "      True\n",
+       "      0.204588\n",
        "    \n",
        "    \n",
        "      3936\n",
-       "      0.213098\n",
        "      True\n",
+       "      0.213098\n",
        "    \n",
        "    \n",
        "      733\n",
-       "      0.217686\n",
        "      True\n",
+       "      0.217686\n",
        "    \n",
        "    \n",
        "      8094\n",
-       "      0.230118\n",
        "      True\n",
+       "      0.230118\n",
        "    \n",
        "  \n",
        "\n",
        ""
       ],
       "text/plain": [
-       "       dark_score  is_dark_issue\n",
-       "34848    0.203922           True\n",
-       "50270    0.204588           True\n",
-       "3936     0.213098           True\n",
-       "733      0.217686           True\n",
-       "8094     0.230118           True"
+       "       is_dark_issue  dark_score\n",
+       "34848           True    0.203922\n",
+       "50270           True    0.204588\n",
+       "3936            True    0.213098\n",
+       "733             True    0.217686\n",
+       "8094            True    0.230118"
       ]
      },
      "execution_count": 26,
@@ -2653,10 +2621,10 @@
    "execution_count": 27,
    "metadata": {
     "execution": {
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-     "iopub.status.busy": "2024-02-13T00:37:29.677985Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.683662Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.683103Z"
+     "iopub.execute_input": "2024-02-13T01:02:37.155873Z",
+     "iopub.status.busy": "2024-02-13T01:02:37.155666Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.162357Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.161820Z"
     },
     "nbsphinx": "hidden"
    },
@@ -2693,10 +2661,10 @@
    "execution_count": 28,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.685941Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.685751Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.889426Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.888952Z"
+     "iopub.execute_input": "2024-02-13T01:02:37.164598Z",
+     "iopub.status.busy": "2024-02-13T01:02:37.164401Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.368662Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.368171Z"
     }
    },
    "outputs": [
@@ -2738,10 +2706,10 @@
    "execution_count": 29,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.891637Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.891305Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.899394Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.898837Z"
+     "iopub.execute_input": "2024-02-13T01:02:37.370798Z",
+     "iopub.status.busy": "2024-02-13T01:02:37.370458Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.378223Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.377660Z"
     }
    },
    "outputs": [
@@ -2766,47 +2734,47 @@
        "  \n",
        "    \n",
        "      \n",
-       "      low_information_score\n",
        "      is_low_information_issue\n",
+       "      low_information_score\n",
        "    \n",
        "  \n",
        "  \n",
        "    \n",
        "      53050\n",
-       "      0.067975\n",
        "      True\n",
+       "      0.067975\n",
        "    \n",
        "    \n",
        "      40875\n",
-       "      0.089929\n",
        "      True\n",
+       "      0.089929\n",
        "    \n",
        "    \n",
        "      9594\n",
-       "      0.092601\n",
        "      True\n",
+       "      0.092601\n",
        "    \n",
        "    \n",
        "      34825\n",
-       "      0.107744\n",
        "      True\n",
+       "      0.107744\n",
        "    \n",
        "    \n",
        "      37530\n",
-       "      0.108516\n",
        "      True\n",
+       "      0.108516\n",
        "    \n",
        "  \n",
        "\n",
        ""
       ],
       "text/plain": [
-       "       low_information_score  is_low_information_issue\n",
-       "53050               0.067975                      True\n",
-       "40875               0.089929                      True\n",
-       "9594                0.092601                      True\n",
-       "34825               0.107744                      True\n",
-       "37530               0.108516                      True"
+       "       is_low_information_issue  low_information_score\n",
+       "53050                      True               0.067975\n",
+       "40875                      True               0.089929\n",
+       "9594                       True               0.092601\n",
+       "34825                      True               0.107744\n",
+       "37530                      True               0.108516"
       ]
      },
      "execution_count": 29,
@@ -2827,10 +2795,10 @@
    "execution_count": 30,
    "metadata": {
     "execution": {
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+     "shell.execute_reply": "2024-02-13T01:02:37.575996Z"
     }
    },
    "outputs": [
@@ -2870,10 +2838,10 @@
    "execution_count": 31,
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2024-02-13T00:37:30.100641Z"
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@@ -3052,7 +3130,7 @@
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+       "value": " 60000/60000 [00:10<00:00, 7438.74 examples/s]"
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+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_8fdeab14761843138de9b721a895adea",
+       "max": 60000.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_bd0a5285b93d46cf987e4b053b932f18",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 60000.0
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-     "fcf64e42e15848e2ae3dab58b8ea108c": {
+     "fa27ad85e9bb40c1ae5234db420a9aa7": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -5395,40 +5397,6 @@
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-     "fede132b65bb4ffba07e243d53a97122": {
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-       "_view_module": "@jupyter-widgets/base",
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diff --git a/master/.doctrees/nbsphinx/tutorials/indepth_overview.ipynb b/master/.doctrees/nbsphinx/tutorials/indepth_overview.ipynb
index 880e905a4..e3aa13e3e 100644
--- a/master/.doctrees/nbsphinx/tutorials/indepth_overview.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/indepth_overview.ipynb
@@ -53,10 +53,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:34.336923Z",
-     "iopub.status.busy": "2024-02-13T00:37:34.336393Z",
-     "iopub.status.idle": "2024-02-13T00:37:35.420786Z",
-     "shell.execute_reply": "2024-02-13T00:37:35.420185Z"
+     "iopub.execute_input": "2024-02-13T01:02:41.833675Z",
+     "iopub.status.busy": "2024-02-13T01:02:41.833203Z",
+     "iopub.status.idle": "2024-02-13T01:02:42.973695Z",
+     "shell.execute_reply": "2024-02-13T01:02:42.973090Z"
     },
     "nbsphinx": "hidden"
    },
@@ -68,7 +68,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -95,10 +95,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2024-02-13T00:37:35.597664Z"
+     "iopub.execute_input": "2024-02-13T01:02:42.976454Z",
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     },
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@@ -234,10 +234,10 @@
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-     "shell.execute_reply": "2024-02-13T00:37:35.611562Z"
+     "iopub.execute_input": "2024-02-13T01:02:43.162168Z",
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+     "shell.execute_reply": "2024-02-13T01:02:43.174410Z"
     },
     "nbsphinx": "hidden"
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@@ -340,10 +340,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:35.614029Z",
-     "iopub.status.busy": "2024-02-13T00:37:35.613636Z",
-     "iopub.status.idle": "2024-02-13T00:37:35.821630Z",
-     "shell.execute_reply": "2024-02-13T00:37:35.821088Z"
+     "iopub.execute_input": "2024-02-13T01:02:43.177058Z",
+     "iopub.status.busy": "2024-02-13T01:02:43.176739Z",
+     "iopub.status.idle": "2024-02-13T01:02:43.415019Z",
+     "shell.execute_reply": "2024-02-13T01:02:43.414405Z"
     }
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    "outputs": [
@@ -393,10 +393,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2024-02-13T00:37:35.851146Z"
+     "iopub.execute_input": "2024-02-13T01:02:43.417532Z",
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+     "shell.execute_reply": "2024-02-13T01:02:43.444787Z"
     }
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    "outputs": [],
@@ -428,10 +428,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2024-02-13T00:37:37.519564Z"
+     "iopub.execute_input": "2024-02-13T01:02:43.447651Z",
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     }
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    "outputs": [
@@ -475,10 +475,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:37.522763Z",
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-     "shell.execute_reply": "2024-02-13T00:37:37.538265Z"
+     "iopub.execute_input": "2024-02-13T01:02:45.183105Z",
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     },
     "scrolled": true
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@@ -489,14 +489,11 @@
      "text": [
       "Here is a summary of the different kinds of issues found in the data:\n",
       "\n",
-      "           issue_type  num_issues\n",
-      "                label          64\n",
-      "              outlier           7\n",
-      "       near_duplicate           6\n",
-      "              non_iid           1\n",
-      "                 null           0\n",
-      "      class_imbalance           0\n",
-      "underperforming_group           0\n",
+      "    issue_type  num_issues\n",
+      "         label          64\n",
+      "       outlier           7\n",
+      "near_duplicate           6\n",
+      "       non_iid           1\n",
       "\n",
       "Dataset Information: num_examples: 250, num_classes: 4\n",
       "\n",
@@ -606,10 +603,10 @@
    "execution_count": 8,
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@@ -728,10 +725,10 @@
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@@ -780,10 +777,10 @@
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@@ -890,10 +887,10 @@
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@@ -930,10 +927,10 @@
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@@ -1399,10 +1396,10 @@
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@@ -1549,10 +1546,10 @@
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@@ -1633,10 +1630,10 @@
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@@ -1696,10 +1693,10 @@
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@@ -1737,10 +1734,10 @@
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@@ -1795,10 +1792,10 @@
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@@ -1849,10 +1846,10 @@
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@@ -1921,10 +1918,10 @@
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@@ -1956,10 +1953,10 @@
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@@ -2016,10 +2013,10 @@
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+     "shell.execute_reply": "2024-02-13T01:02:47.718779Z"
     },
     "id": "WETRL74tE_sU"
    },
@@ -2054,10 +2051,10 @@
    "execution_count": 23,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.986424Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.986016Z",
-     "iopub.status.idle": "2024-02-13T00:37:40.152086Z",
-     "shell.execute_reply": "2024-02-13T00:37:40.151450Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.721525Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.721161Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.914563Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.913919Z"
     },
     "id": "kCfdx2gOLmXS"
    },
@@ -2219,10 +2216,10 @@
    "execution_count": 24,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:40.154261Z",
-     "iopub.status.busy": "2024-02-13T00:37:40.154028Z",
-     "iopub.status.idle": "2024-02-13T00:37:40.160333Z",
-     "shell.execute_reply": "2024-02-13T00:37:40.159779Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.917096Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.916711Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.922691Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.922142Z"
     },
     "id": "-uogYRWFYnuu"
    },
@@ -2276,10 +2273,10 @@
    "execution_count": 25,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:40.162300Z",
-     "iopub.status.busy": "2024-02-13T00:37:40.161998Z",
-     "iopub.status.idle": "2024-02-13T00:37:40.381020Z",
-     "shell.execute_reply": "2024-02-13T00:37:40.380421Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.924839Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.924517Z",
+     "iopub.status.idle": "2024-02-13T01:02:48.145432Z",
+     "shell.execute_reply": "2024-02-13T01:02:48.144840Z"
     },
     "id": "pG-ljrmcYp9Q"
    },
@@ -2326,10 +2323,10 @@
    "execution_count": 26,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:40.383322Z",
-     "iopub.status.busy": "2024-02-13T00:37:40.383000Z",
-     "iopub.status.idle": "2024-02-13T00:37:41.471029Z",
-     "shell.execute_reply": "2024-02-13T00:37:41.470469Z"
+     "iopub.execute_input": "2024-02-13T01:02:48.147699Z",
+     "iopub.status.busy": "2024-02-13T01:02:48.147291Z",
+     "iopub.status.idle": "2024-02-13T01:02:49.223548Z",
+     "shell.execute_reply": "2024-02-13T01:02:49.222908Z"
     },
     "id": "wL3ngCnuLEWd"
    },
diff --git a/master/.doctrees/nbsphinx/tutorials/multiannotator.ipynb b/master/.doctrees/nbsphinx/tutorials/multiannotator.ipynb
index fcc15b91e..2c00a3472 100644
--- a/master/.doctrees/nbsphinx/tutorials/multiannotator.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/multiannotator.ipynb
@@ -89,10 +89,10 @@
    "id": "a3ddc95f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:44.932005Z",
-     "iopub.status.busy": "2024-02-13T00:37:44.931601Z",
-     "iopub.status.idle": "2024-02-13T00:37:45.972699Z",
-     "shell.execute_reply": "2024-02-13T00:37:45.972092Z"
+     "iopub.execute_input": "2024-02-13T01:02:52.661602Z",
+     "iopub.status.busy": "2024-02-13T01:02:52.661190Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.734707Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.734066Z"
     },
     "nbsphinx": "hidden"
    },
@@ -102,7 +102,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -136,10 +136,10 @@
    "id": "c4efd119",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:45.975225Z",
-     "iopub.status.busy": "2024-02-13T00:37:45.974955Z",
-     "iopub.status.idle": "2024-02-13T00:37:45.978111Z",
-     "shell.execute_reply": "2024-02-13T00:37:45.977577Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.737582Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.737271Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.740704Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.740129Z"
     }
    },
    "outputs": [],
@@ -264,10 +264,10 @@
    "id": "c37c0a69",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:45.980351Z",
-     "iopub.status.busy": "2024-02-13T00:37:45.979885Z",
-     "iopub.status.idle": "2024-02-13T00:37:45.987655Z",
-     "shell.execute_reply": "2024-02-13T00:37:45.987087Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.742946Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.742601Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.750330Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.749869Z"
     },
     "nbsphinx": "hidden"
    },
@@ -351,10 +351,10 @@
    "id": "99f69523",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:45.989596Z",
-     "iopub.status.busy": "2024-02-13T00:37:45.989277Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.036506Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.036090Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.752459Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.752125Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.800557Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.800055Z"
     }
    },
    "outputs": [],
@@ -380,10 +380,10 @@
    "id": "8f241c16",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.038619Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.038244Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.055804Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.055338Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.802985Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.802640Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.820098Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.819649Z"
     }
    },
    "outputs": [
@@ -598,10 +598,10 @@
    "id": "4f0819ba",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.057855Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.057526Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.061414Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.060976Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.822293Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.821960Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.825813Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.825373Z"
     }
    },
    "outputs": [
@@ -672,10 +672,10 @@
    "id": "d009f347",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.063516Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.063128Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.092469Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.091907Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.827796Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.827641Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.854664Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.854145Z"
     }
    },
    "outputs": [],
@@ -699,10 +699,10 @@
    "id": "cbd1e415",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.094643Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.094316Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.120466Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.120024Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.857515Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.857114Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.884830Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.884388Z"
     }
    },
    "outputs": [],
@@ -739,10 +739,10 @@
    "id": "6ca92617",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.122412Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.122096Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.897477Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.896981Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.886959Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.886631Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.700403Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.699824Z"
     }
    },
    "outputs": [],
@@ -772,10 +772,10 @@
    "id": "bf945113",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.900018Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.899596Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.906288Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.905738Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.703078Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.702551Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.709491Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.708927Z"
     },
     "scrolled": true
    },
@@ -886,10 +886,10 @@
    "id": "14251ee0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.908268Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.907956Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.920189Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.919649Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.711588Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.711258Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.723565Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.723092Z"
     }
    },
    "outputs": [
@@ -1139,10 +1139,10 @@
    "id": "efe16638",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.922098Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.921787Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.928124Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.927682Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.725578Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.725251Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.731542Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.731090Z"
     },
     "scrolled": true
    },
@@ -1316,10 +1316,10 @@
    "id": "abd0fb0b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.930079Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.929760Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.932903Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.932479Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.733517Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.733188Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.735876Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.735414Z"
     }
    },
    "outputs": [],
@@ -1341,10 +1341,10 @@
    "id": "cdf061df",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.934798Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.934474Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.937711Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.937181Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.737822Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.737505Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.741036Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.740591Z"
     },
     "scrolled": true
    },
@@ -1396,10 +1396,10 @@
    "id": "08949890",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.939701Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.939386Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.941815Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.941384Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.743034Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.742705Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.745337Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.744893Z"
     }
    },
    "outputs": [],
@@ -1423,10 +1423,10 @@
    "id": "6948b073",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.943801Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.943429Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.947682Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.947148Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.747247Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.746933Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.751016Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.750516Z"
     }
    },
    "outputs": [
@@ -1481,10 +1481,10 @@
    "id": "6f8e6914",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.949625Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.949310Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.978169Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.977598Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.753149Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.752751Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.781554Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.780971Z"
     }
    },
    "outputs": [],
@@ -1527,10 +1527,10 @@
    "id": "b806d2ea",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.980456Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.980036Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.984796Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.984246Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.783903Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.783584Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.788275Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.787745Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/.doctrees/nbsphinx/tutorials/multilabel_classification.ipynb b/master/.doctrees/nbsphinx/tutorials/multilabel_classification.ipynb
index 0e1a55f3f..f029d0169 100644
--- a/master/.doctrees/nbsphinx/tutorials/multilabel_classification.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/multilabel_classification.ipynb
@@ -64,10 +64,10 @@
    "id": "7383d024-8273-4039-bccd-aab3020d331f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:50.650771Z",
-     "iopub.status.busy": "2024-02-13T00:37:50.650550Z",
-     "iopub.status.idle": "2024-02-13T00:37:51.774800Z",
-     "shell.execute_reply": "2024-02-13T00:37:51.774125Z"
+     "iopub.execute_input": "2024-02-13T01:02:58.768811Z",
+     "iopub.status.busy": "2024-02-13T01:02:58.768396Z",
+     "iopub.status.idle": "2024-02-13T01:02:59.880006Z",
+     "shell.execute_reply": "2024-02-13T01:02:59.879407Z"
     },
     "nbsphinx": "hidden"
    },
@@ -79,7 +79,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -105,10 +105,10 @@
    "id": "bf9101d8-b1a9-4305-b853-45aaf3d67a69",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:51.777390Z",
-     "iopub.status.busy": "2024-02-13T00:37:51.777090Z",
-     "iopub.status.idle": "2024-02-13T00:37:51.979058Z",
-     "shell.execute_reply": "2024-02-13T00:37:51.978498Z"
+     "iopub.execute_input": "2024-02-13T01:02:59.882450Z",
+     "iopub.status.busy": "2024-02-13T01:02:59.882189Z",
+     "iopub.status.idle": "2024-02-13T01:03:00.080766Z",
+     "shell.execute_reply": "2024-02-13T01:03:00.080087Z"
     }
    },
    "outputs": [],
@@ -268,10 +268,10 @@
    "id": "e8ff5c2f-bd52-44aa-b307-b2b634147c68",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:51.981825Z",
-     "iopub.status.busy": "2024-02-13T00:37:51.981245Z",
-     "iopub.status.idle": "2024-02-13T00:37:51.994150Z",
-     "shell.execute_reply": "2024-02-13T00:37:51.993656Z"
+     "iopub.execute_input": "2024-02-13T01:03:00.083792Z",
+     "iopub.status.busy": "2024-02-13T01:03:00.083150Z",
+     "iopub.status.idle": "2024-02-13T01:03:00.096677Z",
+     "shell.execute_reply": "2024-02-13T01:03:00.096078Z"
     },
     "nbsphinx": "hidden"
    },
@@ -407,10 +407,10 @@
    "id": "dac65d3b-51e8-4682-b829-beab610b56d6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:51.996322Z",
-     "iopub.status.busy": "2024-02-13T00:37:51.995977Z",
-     "iopub.status.idle": "2024-02-13T00:37:54.679288Z",
-     "shell.execute_reply": "2024-02-13T00:37:54.678681Z"
+     "iopub.execute_input": "2024-02-13T01:03:00.099005Z",
+     "iopub.status.busy": "2024-02-13T01:03:00.098612Z",
+     "iopub.status.idle": "2024-02-13T01:03:02.722167Z",
+     "shell.execute_reply": "2024-02-13T01:03:02.721597Z"
     }
    },
    "outputs": [
@@ -454,10 +454,10 @@
    "id": "b5fa99a9-2583-4cd0-9d40-015f698cdb23",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:54.681640Z",
-     "iopub.status.busy": "2024-02-13T00:37:54.681268Z",
-     "iopub.status.idle": "2024-02-13T00:37:56.039215Z",
-     "shell.execute_reply": "2024-02-13T00:37:56.038664Z"
+     "iopub.execute_input": "2024-02-13T01:03:02.724722Z",
+     "iopub.status.busy": "2024-02-13T01:03:02.724201Z",
+     "iopub.status.idle": "2024-02-13T01:03:04.069993Z",
+     "shell.execute_reply": "2024-02-13T01:03:04.069438Z"
     }
    },
    "outputs": [],
@@ -499,10 +499,10 @@
    "id": "ac1a60df",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:56.041719Z",
-     "iopub.status.busy": "2024-02-13T00:37:56.041286Z",
-     "iopub.status.idle": "2024-02-13T00:37:56.045310Z",
-     "shell.execute_reply": "2024-02-13T00:37:56.044765Z"
+     "iopub.execute_input": "2024-02-13T01:03:04.072445Z",
+     "iopub.status.busy": "2024-02-13T01:03:04.072108Z",
+     "iopub.status.idle": "2024-02-13T01:03:04.075799Z",
+     "shell.execute_reply": "2024-02-13T01:03:04.075259Z"
     }
    },
    "outputs": [
@@ -544,10 +544,10 @@
    "id": "d09115b6-ad44-474f-9c8a-85a459586439",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:56.047526Z",
-     "iopub.status.busy": "2024-02-13T00:37:56.047149Z",
-     "iopub.status.idle": "2024-02-13T00:37:57.846739Z",
-     "shell.execute_reply": "2024-02-13T00:37:57.846141Z"
+     "iopub.execute_input": "2024-02-13T01:03:04.077763Z",
+     "iopub.status.busy": "2024-02-13T01:03:04.077443Z",
+     "iopub.status.idle": "2024-02-13T01:03:05.915145Z",
+     "shell.execute_reply": "2024-02-13T01:03:05.914526Z"
     }
    },
    "outputs": [
@@ -594,10 +594,10 @@
    "id": "c18dd83b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:57.849517Z",
-     "iopub.status.busy": "2024-02-13T00:37:57.848710Z",
-     "iopub.status.idle": "2024-02-13T00:37:57.856343Z",
-     "shell.execute_reply": "2024-02-13T00:37:57.855894Z"
+     "iopub.execute_input": "2024-02-13T01:03:05.917885Z",
+     "iopub.status.busy": "2024-02-13T01:03:05.917254Z",
+     "iopub.status.idle": "2024-02-13T01:03:05.924933Z",
+     "shell.execute_reply": "2024-02-13T01:03:05.924469Z"
     }
    },
    "outputs": [
@@ -633,10 +633,10 @@
    "id": "fffa88f6-84d7-45fe-8214-0e22079a06d1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:57.858417Z",
-     "iopub.status.busy": "2024-02-13T00:37:57.858103Z",
-     "iopub.status.idle": "2024-02-13T00:38:00.434248Z",
-     "shell.execute_reply": "2024-02-13T00:38:00.433629Z"
+     "iopub.execute_input": "2024-02-13T01:03:05.926896Z",
+     "iopub.status.busy": "2024-02-13T01:03:05.926639Z",
+     "iopub.status.idle": "2024-02-13T01:03:08.486417Z",
+     "shell.execute_reply": "2024-02-13T01:03:08.485824Z"
     }
    },
    "outputs": [
@@ -671,10 +671,10 @@
    "id": "c1198575",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:00.436547Z",
-     "iopub.status.busy": "2024-02-13T00:38:00.436204Z",
-     "iopub.status.idle": "2024-02-13T00:38:00.439580Z",
-     "shell.execute_reply": "2024-02-13T00:38:00.439055Z"
+     "iopub.execute_input": "2024-02-13T01:03:08.488686Z",
+     "iopub.status.busy": "2024-02-13T01:03:08.488363Z",
+     "iopub.status.idle": "2024-02-13T01:03:08.492007Z",
+     "shell.execute_reply": "2024-02-13T01:03:08.491449Z"
     }
    },
    "outputs": [
@@ -721,10 +721,10 @@
    "id": "49161b19-7625-4fb7-add9-607d91a7eca1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:00.441604Z",
-     "iopub.status.busy": "2024-02-13T00:38:00.441278Z",
-     "iopub.status.idle": "2024-02-13T00:38:00.445327Z",
-     "shell.execute_reply": "2024-02-13T00:38:00.444780Z"
+     "iopub.execute_input": "2024-02-13T01:03:08.494000Z",
+     "iopub.status.busy": "2024-02-13T01:03:08.493695Z",
+     "iopub.status.idle": "2024-02-13T01:03:08.498016Z",
+     "shell.execute_reply": "2024-02-13T01:03:08.497458Z"
     }
    },
    "outputs": [],
@@ -752,10 +752,10 @@
    "id": "d1a2c008",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:00.447305Z",
-     "iopub.status.busy": "2024-02-13T00:38:00.446979Z",
-     "iopub.status.idle": "2024-02-13T00:38:00.450668Z",
-     "shell.execute_reply": "2024-02-13T00:38:00.450247Z"
+     "iopub.execute_input": "2024-02-13T01:03:08.500025Z",
+     "iopub.status.busy": "2024-02-13T01:03:08.499720Z",
+     "iopub.status.idle": "2024-02-13T01:03:08.502936Z",
+     "shell.execute_reply": "2024-02-13T01:03:08.502394Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/.doctrees/nbsphinx/tutorials/object_detection.ipynb b/master/.doctrees/nbsphinx/tutorials/object_detection.ipynb
index 15426f4ed..108bde32a 100644
--- a/master/.doctrees/nbsphinx/tutorials/object_detection.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/object_detection.ipynb
@@ -70,10 +70,10 @@
    "id": "0ba0dc70",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:02.954217Z",
-     "iopub.status.busy": "2024-02-13T00:38:02.954031Z",
-     "iopub.status.idle": "2024-02-13T00:38:04.091043Z",
-     "shell.execute_reply": "2024-02-13T00:38:04.090401Z"
+     "iopub.execute_input": "2024-02-13T01:03:11.142056Z",
+     "iopub.status.busy": "2024-02-13T01:03:11.141857Z",
+     "iopub.status.idle": "2024-02-13T01:03:12.303193Z",
+     "shell.execute_reply": "2024-02-13T01:03:12.302666Z"
     },
     "nbsphinx": "hidden"
    },
@@ -83,7 +83,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -109,10 +109,10 @@
    "id": "c90449c8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:04.093582Z",
-     "iopub.status.busy": "2024-02-13T00:38:04.093297Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.237712Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.237027Z"
+     "iopub.execute_input": "2024-02-13T01:03:12.305972Z",
+     "iopub.status.busy": "2024-02-13T01:03:12.305454Z",
+     "iopub.status.idle": "2024-02-13T01:03:13.728705Z",
+     "shell.execute_reply": "2024-02-13T01:03:13.728015Z"
     }
    },
    "outputs": [],
@@ -130,10 +130,10 @@
    "id": "df8be4c6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:05.240179Z",
-     "iopub.status.busy": "2024-02-13T00:38:05.239978Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.243407Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.242873Z"
+     "iopub.execute_input": "2024-02-13T01:03:13.731213Z",
+     "iopub.status.busy": "2024-02-13T01:03:13.731013Z",
+     "iopub.status.idle": "2024-02-13T01:03:13.734130Z",
+     "shell.execute_reply": "2024-02-13T01:03:13.733674Z"
     }
    },
    "outputs": [],
@@ -169,10 +169,10 @@
    "id": "2e9ffd6f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:05.245459Z",
-     "iopub.status.busy": "2024-02-13T00:38:05.245057Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.252238Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.251811Z"
+     "iopub.execute_input": "2024-02-13T01:03:13.736193Z",
+     "iopub.status.busy": "2024-02-13T01:03:13.735849Z",
+     "iopub.status.idle": "2024-02-13T01:03:13.742674Z",
+     "shell.execute_reply": "2024-02-13T01:03:13.742242Z"
     }
    },
    "outputs": [],
@@ -198,10 +198,10 @@
    "id": "56705562",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:05.254315Z",
-     "iopub.status.busy": "2024-02-13T00:38:05.254000Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.742554Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.741944Z"
+     "iopub.execute_input": "2024-02-13T01:03:13.744769Z",
+     "iopub.status.busy": "2024-02-13T01:03:13.744583Z",
+     "iopub.status.idle": "2024-02-13T01:03:14.236517Z",
+     "shell.execute_reply": "2024-02-13T01:03:14.235931Z"
     },
     "scrolled": true
    },
@@ -242,10 +242,10 @@
    "id": "b08144d7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:05.744999Z",
-     "iopub.status.busy": "2024-02-13T00:38:05.744654Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.749919Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.749469Z"
+     "iopub.execute_input": "2024-02-13T01:03:14.239143Z",
+     "iopub.status.busy": "2024-02-13T01:03:14.238954Z",
+     "iopub.status.idle": "2024-02-13T01:03:14.244593Z",
+     "shell.execute_reply": "2024-02-13T01:03:14.244094Z"
     }
    },
    "outputs": [
@@ -497,10 +497,10 @@
    "id": "3d70bec6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:05.752019Z",
-     "iopub.status.busy": "2024-02-13T00:38:05.751694Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.755489Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.754933Z"
+     "iopub.execute_input": "2024-02-13T01:03:14.246480Z",
+     "iopub.status.busy": "2024-02-13T01:03:14.246305Z",
+     "iopub.status.idle": "2024-02-13T01:03:14.250185Z",
+     "shell.execute_reply": "2024-02-13T01:03:14.249760Z"
     }
    },
    "outputs": [
@@ -557,10 +557,10 @@
    "id": "4caa635d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:05.757600Z",
-     "iopub.status.busy": "2024-02-13T00:38:05.757207Z",
-     "iopub.status.idle": "2024-02-13T00:38:06.566098Z",
-     "shell.execute_reply": "2024-02-13T00:38:06.565532Z"
+     "iopub.execute_input": "2024-02-13T01:03:14.252075Z",
+     "iopub.status.busy": "2024-02-13T01:03:14.251894Z",
+     "iopub.status.idle": "2024-02-13T01:03:14.950221Z",
+     "shell.execute_reply": "2024-02-13T01:03:14.949600Z"
     }
    },
    "outputs": [
@@ -616,10 +616,10 @@
    "id": "a9b4c590",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:06.568266Z",
-     "iopub.status.busy": "2024-02-13T00:38:06.568043Z",
-     "iopub.status.idle": "2024-02-13T00:38:06.749946Z",
-     "shell.execute_reply": "2024-02-13T00:38:06.749427Z"
+     "iopub.execute_input": "2024-02-13T01:03:14.952419Z",
+     "iopub.status.busy": "2024-02-13T01:03:14.952219Z",
+     "iopub.status.idle": "2024-02-13T01:03:15.130259Z",
+     "shell.execute_reply": "2024-02-13T01:03:15.129745Z"
     }
    },
    "outputs": [
@@ -660,10 +660,10 @@
    "id": "ffd9ebcc",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:06.752333Z",
-     "iopub.status.busy": "2024-02-13T00:38:06.751901Z",
-     "iopub.status.idle": "2024-02-13T00:38:06.756259Z",
-     "shell.execute_reply": "2024-02-13T00:38:06.755830Z"
+     "iopub.execute_input": "2024-02-13T01:03:15.132867Z",
+     "iopub.status.busy": "2024-02-13T01:03:15.132537Z",
+     "iopub.status.idle": "2024-02-13T01:03:15.136795Z",
+     "shell.execute_reply": "2024-02-13T01:03:15.136356Z"
     }
    },
    "outputs": [
@@ -700,10 +700,10 @@
    "id": "4dd46d67",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:06.758202Z",
-     "iopub.status.busy": "2024-02-13T00:38:06.757905Z",
-     "iopub.status.idle": "2024-02-13T00:38:07.208423Z",
-     "shell.execute_reply": "2024-02-13T00:38:07.207864Z"
+     "iopub.execute_input": "2024-02-13T01:03:15.138839Z",
+     "iopub.status.busy": "2024-02-13T01:03:15.138454Z",
+     "iopub.status.idle": "2024-02-13T01:03:15.596289Z",
+     "shell.execute_reply": "2024-02-13T01:03:15.595728Z"
     }
    },
    "outputs": [
@@ -762,10 +762,10 @@
    "id": "ceec2394",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:07.211175Z",
-     "iopub.status.busy": "2024-02-13T00:38:07.210858Z",
-     "iopub.status.idle": "2024-02-13T00:38:07.543264Z",
-     "shell.execute_reply": "2024-02-13T00:38:07.542696Z"
+     "iopub.execute_input": "2024-02-13T01:03:15.599042Z",
+     "iopub.status.busy": "2024-02-13T01:03:15.598713Z",
+     "iopub.status.idle": "2024-02-13T01:03:15.931718Z",
+     "shell.execute_reply": "2024-02-13T01:03:15.931130Z"
     }
    },
    "outputs": [
@@ -812,10 +812,10 @@
    "id": "94f82b0d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:07.545979Z",
-     "iopub.status.busy": "2024-02-13T00:38:07.545565Z",
-     "iopub.status.idle": "2024-02-13T00:38:07.912099Z",
-     "shell.execute_reply": "2024-02-13T00:38:07.911498Z"
+     "iopub.execute_input": "2024-02-13T01:03:15.934039Z",
+     "iopub.status.busy": "2024-02-13T01:03:15.933701Z",
+     "iopub.status.idle": "2024-02-13T01:03:16.295190Z",
+     "shell.execute_reply": "2024-02-13T01:03:16.294624Z"
     }
    },
    "outputs": [
@@ -862,10 +862,10 @@
    "id": "1ea18c5d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:07.914949Z",
-     "iopub.status.busy": "2024-02-13T00:38:07.914582Z",
-     "iopub.status.idle": "2024-02-13T00:38:08.357594Z",
-     "shell.execute_reply": "2024-02-13T00:38:08.357052Z"
+     "iopub.execute_input": "2024-02-13T01:03:16.298397Z",
+     "iopub.status.busy": "2024-02-13T01:03:16.298037Z",
+     "iopub.status.idle": "2024-02-13T01:03:16.738397Z",
+     "shell.execute_reply": "2024-02-13T01:03:16.737826Z"
     }
    },
    "outputs": [
@@ -925,10 +925,10 @@
    "id": "7e770d23",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:08.361613Z",
-     "iopub.status.busy": "2024-02-13T00:38:08.361414Z",
-     "iopub.status.idle": "2024-02-13T00:38:08.787747Z",
-     "shell.execute_reply": "2024-02-13T00:38:08.787133Z"
+     "iopub.execute_input": "2024-02-13T01:03:16.742750Z",
+     "iopub.status.busy": "2024-02-13T01:03:16.742408Z",
+     "iopub.status.idle": "2024-02-13T01:03:17.168900Z",
+     "shell.execute_reply": "2024-02-13T01:03:17.168305Z"
     }
    },
    "outputs": [
@@ -971,10 +971,10 @@
    "id": "57e84a27",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:08.790980Z",
-     "iopub.status.busy": "2024-02-13T00:38:08.790532Z",
-     "iopub.status.idle": "2024-02-13T00:38:09.010584Z",
-     "shell.execute_reply": "2024-02-13T00:38:09.009975Z"
+     "iopub.execute_input": "2024-02-13T01:03:17.172162Z",
+     "iopub.status.busy": "2024-02-13T01:03:17.171719Z",
+     "iopub.status.idle": "2024-02-13T01:03:17.363729Z",
+     "shell.execute_reply": "2024-02-13T01:03:17.363164Z"
     }
    },
    "outputs": [
@@ -1017,10 +1017,10 @@
    "id": "0302818a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:09.013031Z",
-     "iopub.status.busy": "2024-02-13T00:38:09.012566Z",
-     "iopub.status.idle": "2024-02-13T00:38:09.194017Z",
-     "shell.execute_reply": "2024-02-13T00:38:09.193435Z"
+     "iopub.execute_input": "2024-02-13T01:03:17.366816Z",
+     "iopub.status.busy": "2024-02-13T01:03:17.366256Z",
+     "iopub.status.idle": "2024-02-13T01:03:17.569906Z",
+     "shell.execute_reply": "2024-02-13T01:03:17.569267Z"
     }
    },
    "outputs": [
@@ -1067,10 +1067,10 @@
    "id": "5cacec81-2adf-46a8-82c5-7ec0185d4356",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:09.196458Z",
-     "iopub.status.busy": "2024-02-13T00:38:09.195907Z",
-     "iopub.status.idle": "2024-02-13T00:38:09.198906Z",
-     "shell.execute_reply": "2024-02-13T00:38:09.198434Z"
+     "iopub.execute_input": "2024-02-13T01:03:17.572554Z",
+     "iopub.status.busy": "2024-02-13T01:03:17.572028Z",
+     "iopub.status.idle": "2024-02-13T01:03:17.575133Z",
+     "shell.execute_reply": "2024-02-13T01:03:17.574708Z"
     }
    },
    "outputs": [],
@@ -1090,10 +1090,10 @@
    "id": "3335b8a3-d0b4-415a-a97d-c203088a124e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:09.200810Z",
-     "iopub.status.busy": "2024-02-13T00:38:09.200636Z",
-     "iopub.status.idle": "2024-02-13T00:38:10.107251Z",
-     "shell.execute_reply": "2024-02-13T00:38:10.106620Z"
+     "iopub.execute_input": "2024-02-13T01:03:17.577176Z",
+     "iopub.status.busy": "2024-02-13T01:03:17.576805Z",
+     "iopub.status.idle": "2024-02-13T01:03:18.520579Z",
+     "shell.execute_reply": "2024-02-13T01:03:18.519995Z"
     }
    },
    "outputs": [
@@ -1172,10 +1172,10 @@
    "id": "9d4b7677-6ebd-447d-b0a1-76e094686628",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:10.109515Z",
-     "iopub.status.busy": "2024-02-13T00:38:10.109333Z",
-     "iopub.status.idle": "2024-02-13T00:38:10.240271Z",
-     "shell.execute_reply": "2024-02-13T00:38:10.239670Z"
+     "iopub.execute_input": "2024-02-13T01:03:18.523127Z",
+     "iopub.status.busy": "2024-02-13T01:03:18.522711Z",
+     "iopub.status.idle": "2024-02-13T01:03:18.672007Z",
+     "shell.execute_reply": "2024-02-13T01:03:18.671522Z"
     }
    },
    "outputs": [
@@ -1214,10 +1214,10 @@
    "id": "59d7ee39-3785-434b-8680-9133014851cd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:10.242595Z",
-     "iopub.status.busy": "2024-02-13T00:38:10.242119Z",
-     "iopub.status.idle": "2024-02-13T00:38:10.423913Z",
-     "shell.execute_reply": "2024-02-13T00:38:10.423360Z"
+     "iopub.execute_input": "2024-02-13T01:03:18.674116Z",
+     "iopub.status.busy": "2024-02-13T01:03:18.673931Z",
+     "iopub.status.idle": "2024-02-13T01:03:18.814206Z",
+     "shell.execute_reply": "2024-02-13T01:03:18.813573Z"
     }
    },
    "outputs": [],
@@ -1266,10 +1266,10 @@
    "id": "47b6a8ff-7a58-4a1f-baee-e6cfe7a85a6d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:10.426135Z",
-     "iopub.status.busy": "2024-02-13T00:38:10.425801Z",
-     "iopub.status.idle": "2024-02-13T00:38:11.193456Z",
-     "shell.execute_reply": "2024-02-13T00:38:11.192845Z"
+     "iopub.execute_input": "2024-02-13T01:03:18.816350Z",
+     "iopub.status.busy": "2024-02-13T01:03:18.816156Z",
+     "iopub.status.idle": "2024-02-13T01:03:19.535673Z",
+     "shell.execute_reply": "2024-02-13T01:03:19.535130Z"
     }
    },
    "outputs": [
@@ -1351,10 +1351,10 @@
    "id": "8ce74938",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:11.195705Z",
-     "iopub.status.busy": "2024-02-13T00:38:11.195361Z",
-     "iopub.status.idle": "2024-02-13T00:38:11.199055Z",
-     "shell.execute_reply": "2024-02-13T00:38:11.198495Z"
+     "iopub.execute_input": "2024-02-13T01:03:19.537795Z",
+     "iopub.status.busy": "2024-02-13T01:03:19.537617Z",
+     "iopub.status.idle": "2024-02-13T01:03:19.541117Z",
+     "shell.execute_reply": "2024-02-13T01:03:19.540711Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/.doctrees/nbsphinx/tutorials/outliers.ipynb b/master/.doctrees/nbsphinx/tutorials/outliers.ipynb
index 85bfdbf77..2fd4d0b8b 100644
--- a/master/.doctrees/nbsphinx/tutorials/outliers.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/outliers.ipynb
@@ -109,10 +109,10 @@
    "id": "2bbebfc8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:13.538819Z",
-     "iopub.status.busy": "2024-02-13T00:38:13.538332Z",
-     "iopub.status.idle": "2024-02-13T00:38:16.310196Z",
-     "shell.execute_reply": "2024-02-13T00:38:16.309618Z"
+     "iopub.execute_input": "2024-02-13T01:03:21.946350Z",
+     "iopub.status.busy": "2024-02-13T01:03:21.946175Z",
+     "iopub.status.idle": "2024-02-13T01:03:24.693428Z",
+     "shell.execute_reply": "2024-02-13T01:03:24.692797Z"
     },
     "nbsphinx": "hidden"
    },
@@ -125,7 +125,7 @@
     "dependencies = [\"matplotlib\", \"torch\", \"torchvision\", \"timm\", \"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -159,10 +159,10 @@
    "id": "4396f544",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:16.312856Z",
-     "iopub.status.busy": "2024-02-13T00:38:16.312401Z",
-     "iopub.status.idle": "2024-02-13T00:38:16.652112Z",
-     "shell.execute_reply": "2024-02-13T00:38:16.651552Z"
+     "iopub.execute_input": "2024-02-13T01:03:24.696184Z",
+     "iopub.status.busy": "2024-02-13T01:03:24.695863Z",
+     "iopub.status.idle": "2024-02-13T01:03:25.047975Z",
+     "shell.execute_reply": "2024-02-13T01:03:25.047451Z"
     }
    },
    "outputs": [],
@@ -188,10 +188,10 @@
    "id": "3792f82e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:16.654843Z",
-     "iopub.status.busy": "2024-02-13T00:38:16.654258Z",
-     "iopub.status.idle": "2024-02-13T00:38:16.658614Z",
-     "shell.execute_reply": "2024-02-13T00:38:16.658201Z"
+     "iopub.execute_input": "2024-02-13T01:03:25.050426Z",
+     "iopub.status.busy": "2024-02-13T01:03:25.050112Z",
+     "iopub.status.idle": "2024-02-13T01:03:25.054262Z",
+     "shell.execute_reply": "2024-02-13T01:03:25.053845Z"
     },
     "nbsphinx": "hidden"
    },
@@ -225,10 +225,10 @@
    "id": "fd853a54",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:16.660663Z",
-     "iopub.status.busy": "2024-02-13T00:38:16.660336Z",
-     "iopub.status.idle": "2024-02-13T00:38:22.677513Z",
-     "shell.execute_reply": "2024-02-13T00:38:22.676909Z"
+     "iopub.execute_input": "2024-02-13T01:03:25.056210Z",
+     "iopub.status.busy": "2024-02-13T01:03:25.056033Z",
+     "iopub.status.idle": "2024-02-13T01:03:29.390845Z",
+     "shell.execute_reply": "2024-02-13T01:03:29.390321Z"
     }
    },
    "outputs": [
@@ -252,7 +252,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "  1%|          | 1343488/170498071 [00:00<00:12, 13419215.78it/s]"
+      "  1%|▏         | 2326528/170498071 [00:00<00:07, 23219298.71it/s]"
      ]
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     {
@@ -260,7 +260,7 @@
      "output_type": "stream",
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       "\r",
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+      "  8%|▊         | 13303808/170498071 [00:00<00:02, 73844881.63it/s]"
      ]
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     {
@@ -268,7 +268,7 @@
      "output_type": "stream",
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+      " 14%|█▍        | 24674304/170498071 [00:00<00:01, 91964167.23it/s]"
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@@ -276,7 +276,7 @@
      "output_type": "stream",
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       "\r",
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+      " 21%|██        | 34963456/170498071 [00:00<00:01, 96191879.75it/s]"
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@@ -284,7 +284,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 27%|██▋       | 45383680/170498071 [00:00<00:01, 99000165.63it/s]"
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@@ -292,7 +292,7 @@
      "output_type": "stream",
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+      " 33%|███▎      | 56393728/170498071 [00:00<00:01, 102767412.84it/s]"
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@@ -300,7 +300,7 @@
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+      " 39%|███▉      | 67141632/170498071 [00:00<00:00, 104252034.08it/s]"
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      "output_type": "stream",
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+      " 46%|████▌     | 77856768/170498071 [00:00<00:00, 105125468.20it/s]"
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@@ -316,7 +316,7 @@
      "output_type": "stream",
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+      " 52%|█████▏    | 88899584/170498071 [00:00<00:00, 106705587.58it/s]"
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@@ -324,7 +324,7 @@
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+      " 58%|█████▊    | 99581952/170498071 [00:01<00:00, 105304746.58it/s]"
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@@ -332,7 +332,7 @@
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+      " 78%|███████▊  | 132677632/170498071 [00:01<00:00, 108681810.16it/s]"
      ]
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@@ -356,7 +356,7 @@
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+      " 84%|████████▍ | 143818752/170498071 [00:01<00:00, 109445329.99it/s]"
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@@ -364,7 +364,7 @@
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     },
     {
@@ -626,10 +498,10 @@
    "id": "9b64e0aa",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:22.679908Z",
-     "iopub.status.busy": "2024-02-13T00:38:22.679558Z",
-     "iopub.status.idle": "2024-02-13T00:38:22.684187Z",
-     "shell.execute_reply": "2024-02-13T00:38:22.683763Z"
+     "iopub.execute_input": "2024-02-13T01:03:29.393043Z",
+     "iopub.status.busy": "2024-02-13T01:03:29.392764Z",
+     "iopub.status.idle": "2024-02-13T01:03:29.397461Z",
+     "shell.execute_reply": "2024-02-13T01:03:29.397032Z"
     },
     "nbsphinx": "hidden"
    },
@@ -680,10 +552,10 @@
    "id": "a00aa3ed",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:22.686206Z",
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-     "iopub.status.idle": "2024-02-13T00:38:23.234419Z",
-     "shell.execute_reply": "2024-02-13T00:38:23.233860Z"
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-       "_model_name": "HBoxModel",
+       "_model_name": "HTMLStyleModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/controls",
+       "_view_module": "@jupyter-widgets/base",
        "_view_module_version": "2.0.0",
-       "_view_name": "HBoxView",
-       "box_style": "",
-       "children": [
-        "IPY_MODEL_1c399fc6dfaf46e78dd6b627dd9ab79e",
-        "IPY_MODEL_91bdb5338d374cb7b81754d69354659a",
-        "IPY_MODEL_eaaf9257d4454c79b003911fddfdcba4"
-       ],
-       "layout": "IPY_MODEL_de53c221b897471d9ee2bad1f34bd6ad",
-       "tabbable": null,
-       "tooltip": null
+       "_view_name": "StyleView",
+       "background": null,
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
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diff --git a/master/.doctrees/nbsphinx/tutorials/regression.ipynb b/master/.doctrees/nbsphinx/tutorials/regression.ipynb
index c43233657..f45de88ba 100644
--- a/master/.doctrees/nbsphinx/tutorials/regression.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/regression.ipynb
@@ -102,10 +102,10 @@
    "id": "2e1af7d8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:56.418963Z",
-     "iopub.status.busy": "2024-02-13T00:38:56.418538Z",
-     "iopub.status.idle": "2024-02-13T00:38:57.502296Z",
-     "shell.execute_reply": "2024-02-13T00:38:57.501688Z"
+     "iopub.execute_input": "2024-02-13T01:04:03.295564Z",
+     "iopub.status.busy": "2024-02-13T01:04:03.295384Z",
+     "iopub.status.idle": "2024-02-13T01:04:04.470389Z",
+     "shell.execute_reply": "2024-02-13T01:04:04.469810Z"
     },
     "nbsphinx": "hidden"
    },
@@ -117,7 +117,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib>=3.6.0\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = \" \".join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -143,10 +143,10 @@
    "id": "4fb10b8f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:57.504994Z",
-     "iopub.status.busy": "2024-02-13T00:38:57.504661Z",
-     "iopub.status.idle": "2024-02-13T00:38:57.522557Z",
-     "shell.execute_reply": "2024-02-13T00:38:57.522014Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.473255Z",
+     "iopub.status.busy": "2024-02-13T01:04:04.472725Z",
+     "iopub.status.idle": "2024-02-13T01:04:04.492603Z",
+     "shell.execute_reply": "2024-02-13T01:04:04.492080Z"
     }
    },
    "outputs": [],
@@ -165,10 +165,10 @@
    "id": "284dc264",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:57.524915Z",
-     "iopub.status.busy": "2024-02-13T00:38:57.524458Z",
-     "iopub.status.idle": "2024-02-13T00:38:57.527466Z",
-     "shell.execute_reply": "2024-02-13T00:38:57.527014Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.495177Z",
+     "iopub.status.busy": "2024-02-13T01:04:04.494663Z",
+     "iopub.status.idle": "2024-02-13T01:04:04.497965Z",
+     "shell.execute_reply": "2024-02-13T01:04:04.497440Z"
     },
     "nbsphinx": "hidden"
    },
@@ -199,10 +199,10 @@
    "id": "0f7450db",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:57.529494Z",
-     "iopub.status.busy": "2024-02-13T00:38:57.529082Z",
-     "iopub.status.idle": "2024-02-13T00:38:57.604240Z",
-     "shell.execute_reply": "2024-02-13T00:38:57.603695Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.500196Z",
+     "iopub.status.busy": "2024-02-13T01:04:04.499813Z",
+     "iopub.status.idle": "2024-02-13T01:04:04.611611Z",
+     "shell.execute_reply": "2024-02-13T01:04:04.610989Z"
     }
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    "outputs": [
@@ -375,10 +375,10 @@
    "id": "55513fed",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:57.606593Z",
-     "iopub.status.busy": "2024-02-13T00:38:57.606282Z",
-     "iopub.status.idle": "2024-02-13T00:38:57.783988Z",
-     "shell.execute_reply": "2024-02-13T00:38:57.783443Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.613792Z",
+     "iopub.status.busy": "2024-02-13T01:04:04.613601Z",
+     "iopub.status.idle": "2024-02-13T01:04:04.805710Z",
+     "shell.execute_reply": "2024-02-13T01:04:04.805077Z"
     },
     "nbsphinx": "hidden"
    },
@@ -418,10 +418,10 @@
    "id": "df5a0f59",
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     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:57.786254Z",
-     "iopub.status.busy": "2024-02-13T00:38:57.786047Z",
-     "iopub.status.idle": "2024-02-13T00:38:58.026415Z",
-     "shell.execute_reply": "2024-02-13T00:38:58.025843Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.808407Z",
+     "iopub.status.busy": "2024-02-13T01:04:04.808098Z",
+     "iopub.status.idle": "2024-02-13T01:04:05.060992Z",
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@@ -457,10 +457,10 @@
    "id": "7af78a8a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:58.028577Z",
-     "iopub.status.busy": "2024-02-13T00:38:58.028250Z",
-     "iopub.status.idle": "2024-02-13T00:38:58.032455Z",
-     "shell.execute_reply": "2024-02-13T00:38:58.032007Z"
+     "iopub.execute_input": "2024-02-13T01:04:05.063164Z",
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+     "iopub.status.idle": "2024-02-13T01:04:05.067821Z",
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@@ -478,10 +478,10 @@
    "id": "9556c624",
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     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:58.034470Z",
-     "iopub.status.busy": "2024-02-13T00:38:58.034154Z",
-     "iopub.status.idle": "2024-02-13T00:38:58.039926Z",
-     "shell.execute_reply": "2024-02-13T00:38:58.039514Z"
+     "iopub.execute_input": "2024-02-13T01:04:05.069776Z",
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    "outputs": [],
@@ -528,10 +528,10 @@
    "id": "3c2f1ccc",
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     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:58.042002Z",
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-     "shell.execute_reply": "2024-02-13T00:38:58.043689Z"
+     "iopub.execute_input": "2024-02-13T01:04:05.078739Z",
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+     "iopub.status.idle": "2024-02-13T01:04:05.081378Z",
+     "shell.execute_reply": "2024-02-13T01:04:05.080921Z"
     }
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    "outputs": [],
@@ -546,10 +546,10 @@
    "id": "7e1b7860",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:58.046106Z",
-     "iopub.status.busy": "2024-02-13T00:38:58.045692Z",
-     "iopub.status.idle": "2024-02-13T00:39:06.553915Z",
-     "shell.execute_reply": "2024-02-13T00:39:06.553250Z"
+     "iopub.execute_input": "2024-02-13T01:04:05.083440Z",
+     "iopub.status.busy": "2024-02-13T01:04:05.083057Z",
+     "iopub.status.idle": "2024-02-13T01:04:13.705031Z",
+     "shell.execute_reply": "2024-02-13T01:04:13.704339Z"
     }
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    "outputs": [],
@@ -573,10 +573,10 @@
    "id": "f407bd69",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:39:06.557117Z",
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-     "shell.execute_reply": "2024-02-13T00:39:06.563063Z"
+     "iopub.execute_input": "2024-02-13T01:04:13.708170Z",
+     "iopub.status.busy": "2024-02-13T01:04:13.707545Z",
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+     "shell.execute_reply": "2024-02-13T01:04:13.714322Z"
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    "outputs": [
@@ -679,10 +679,10 @@
    "id": "f7385336",
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     "execution": {
-     "iopub.execute_input": "2024-02-13T00:39:06.565703Z",
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+     "iopub.execute_input": "2024-02-13T01:04:13.717129Z",
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@@ -697,10 +697,10 @@
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@@ -735,10 +735,10 @@
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@@ -757,10 +757,10 @@
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@@ -884,10 +884,10 @@
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-     "iopub.execute_input": "2024-02-13T00:39:06.590154Z",
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@@ -922,10 +922,10 @@
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@@ -964,10 +964,10 @@
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@@ -1023,10 +1023,10 @@
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@@ -1042,10 +1042,10 @@
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@@ -1080,10 +1080,10 @@
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@@ -1190,10 +1190,10 @@
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@@ -1218,10 +1218,10 @@
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@@ -1265,10 +1265,10 @@
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@@ -1377,10 +1377,10 @@
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-     "shell.execute_reply": "2024-02-13T00:39:12.983711Z"
+     "iopub.execute_input": "2024-02-13T01:04:20.226697Z",
+     "iopub.status.busy": "2024-02-13T01:04:20.226371Z",
+     "iopub.status.idle": "2024-02-13T01:04:20.292062Z",
+     "shell.execute_reply": "2024-02-13T01:04:20.291419Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/.doctrees/nbsphinx/tutorials/segmentation.ipynb b/master/.doctrees/nbsphinx/tutorials/segmentation.ipynb
index 2c84a07e4..5a19416ec 100644
--- a/master/.doctrees/nbsphinx/tutorials/segmentation.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/segmentation.ipynb
@@ -61,10 +61,10 @@
    "id": "ae8a08e0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:39:16.016581Z",
-     "iopub.status.busy": "2024-02-13T00:39:16.016411Z",
-     "iopub.status.idle": "2024-02-13T00:39:17.846185Z",
-     "shell.execute_reply": "2024-02-13T00:39:17.845532Z"
+     "iopub.execute_input": "2024-02-13T01:04:24.456211Z",
+     "iopub.status.busy": "2024-02-13T01:04:24.456033Z",
+     "iopub.status.idle": "2024-02-13T01:04:26.961154Z",
+     "shell.execute_reply": "2024-02-13T01:04:26.960465Z"
     }
    },
    "outputs": [],
@@ -79,10 +79,10 @@
    "id": "58fd4c55",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:39:17.848857Z",
-     "iopub.status.busy": "2024-02-13T00:39:17.848507Z",
-     "iopub.status.idle": "2024-02-13T00:40:20.168637Z",
-     "shell.execute_reply": "2024-02-13T00:40:20.167980Z"
+     "iopub.execute_input": "2024-02-13T01:04:26.963827Z",
+     "iopub.status.busy": "2024-02-13T01:04:26.963606Z",
+     "iopub.status.idle": "2024-02-13T01:06:05.695134Z",
+     "shell.execute_reply": "2024-02-13T01:06:05.694398Z"
     }
    },
    "outputs": [],
@@ -97,10 +97,10 @@
    "id": "439b0305",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:20.170997Z",
-     "iopub.status.busy": "2024-02-13T00:40:20.170812Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.217733Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.217103Z"
+     "iopub.execute_input": "2024-02-13T01:06:05.697918Z",
+     "iopub.status.busy": "2024-02-13T01:06:05.697527Z",
+     "iopub.status.idle": "2024-02-13T01:06:06.776866Z",
+     "shell.execute_reply": "2024-02-13T01:06:06.776248Z"
     },
     "nbsphinx": "hidden"
    },
@@ -111,7 +111,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -137,10 +137,10 @@
    "id": "a1349304",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:21.220218Z",
-     "iopub.status.busy": "2024-02-13T00:40:21.219949Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.223254Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.222838Z"
+     "iopub.execute_input": "2024-02-13T01:06:06.779676Z",
+     "iopub.status.busy": "2024-02-13T01:06:06.779211Z",
+     "iopub.status.idle": "2024-02-13T01:06:06.782966Z",
+     "shell.execute_reply": "2024-02-13T01:06:06.782526Z"
     }
    },
    "outputs": [],
@@ -203,10 +203,10 @@
    "id": "07dc5678",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:21.225373Z",
-     "iopub.status.busy": "2024-02-13T00:40:21.225050Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.228867Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.228454Z"
+     "iopub.execute_input": "2024-02-13T01:06:06.784992Z",
+     "iopub.status.busy": "2024-02-13T01:06:06.784723Z",
+     "iopub.status.idle": "2024-02-13T01:06:06.788767Z",
+     "shell.execute_reply": "2024-02-13T01:06:06.788300Z"
     }
    },
    "outputs": [
@@ -247,10 +247,10 @@
    "id": "25ebe22a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:21.230771Z",
-     "iopub.status.busy": "2024-02-13T00:40:21.230493Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.234013Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.233591Z"
+     "iopub.execute_input": "2024-02-13T01:06:06.790688Z",
+     "iopub.status.busy": "2024-02-13T01:06:06.790377Z",
+     "iopub.status.idle": "2024-02-13T01:06:06.793892Z",
+     "shell.execute_reply": "2024-02-13T01:06:06.793425Z"
     }
    },
    "outputs": [
@@ -290,10 +290,10 @@
    "id": "3faedea9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:21.235957Z",
-     "iopub.status.busy": "2024-02-13T00:40:21.235652Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.238285Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.237864Z"
+     "iopub.execute_input": "2024-02-13T01:06:06.795857Z",
+     "iopub.status.busy": "2024-02-13T01:06:06.795538Z",
+     "iopub.status.idle": "2024-02-13T01:06:06.798235Z",
+     "shell.execute_reply": "2024-02-13T01:06:06.797802Z"
     }
    },
    "outputs": [],
@@ -333,17 +333,17 @@
    "id": "2c2ad9ad",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:21.240256Z",
-     "iopub.status.busy": "2024-02-13T00:40:21.239953Z",
-     "iopub.status.idle": "2024-02-13T00:41:37.524238Z",
-     "shell.execute_reply": "2024-02-13T00:41:37.523624Z"
+     "iopub.execute_input": "2024-02-13T01:06:06.800327Z",
+     "iopub.status.busy": "2024-02-13T01:06:06.799926Z",
+     "iopub.status.idle": "2024-02-13T01:07:22.998914Z",
+     "shell.execute_reply": "2024-02-13T01:07:22.998356Z"
     }
    },
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4c4ea88a0faa4e7994b8500868517daa",
+       "model_id": "a9b1e8dc109a4f008f633ecea989f488",
        "version_major": 2,
        "version_minor": 0
       },
@@ -357,7 +357,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6ea9834dc3244dd786fd5e8ff97b24a6",
+       "model_id": "780e886400954a6295d03c905586d673",
        "version_major": 2,
        "version_minor": 0
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@@ -400,10 +400,10 @@
    "id": "95dc7268",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:41:37.526978Z",
-     "iopub.status.busy": "2024-02-13T00:41:37.526601Z",
-     "iopub.status.idle": "2024-02-13T00:41:38.162461Z",
-     "shell.execute_reply": "2024-02-13T00:41:38.161972Z"
+     "iopub.execute_input": "2024-02-13T01:07:23.001525Z",
+     "iopub.status.busy": "2024-02-13T01:07:23.001327Z",
+     "iopub.status.idle": "2024-02-13T01:07:23.692603Z",
+     "shell.execute_reply": "2024-02-13T01:07:23.692017Z"
     }
    },
    "outputs": [
@@ -446,10 +446,10 @@
    "id": "57fed473",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:41:38.164799Z",
-     "iopub.status.busy": "2024-02-13T00:41:38.164336Z",
-     "iopub.status.idle": "2024-02-13T00:41:40.886173Z",
-     "shell.execute_reply": "2024-02-13T00:41:40.885669Z"
+     "iopub.execute_input": "2024-02-13T01:07:23.694960Z",
+     "iopub.status.busy": "2024-02-13T01:07:23.694489Z",
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+     "shell.execute_reply": "2024-02-13T01:07:26.427975Z"
     }
    },
    "outputs": [
@@ -519,10 +519,10 @@
    "id": "e4a006bd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:41:40.888366Z",
-     "iopub.status.busy": "2024-02-13T00:41:40.888013Z",
-     "iopub.status.idle": "2024-02-13T00:42:12.691599Z",
-     "shell.execute_reply": "2024-02-13T00:42:12.691127Z"
+     "iopub.execute_input": "2024-02-13T01:07:26.430734Z",
+     "iopub.status.busy": "2024-02-13T01:07:26.430400Z",
+     "iopub.status.idle": "2024-02-13T01:07:58.911826Z",
+     "shell.execute_reply": "2024-02-13T01:07:58.911253Z"
     }
    },
    "outputs": [
@@ -539,7 +539,7 @@
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+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_0068535838c14b828d503f31aef6cbdd",
+       "placeholder": "​",
+       "style": "IPY_MODEL_952501edbe2342999201781c8f40fd58",
+       "tabbable": null,
+       "tooltip": null,
+       "value": "number of examples processed for estimating thresholds: 100%"
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-     "dea3296f12ae42428ac7465bc6dbc3d6": {
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        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLModel",
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        "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "HTMLView",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
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-       "layout": "IPY_MODEL_a3fcaef394c14ef080481ae7b041528e",
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-       "style": "IPY_MODEL_cce2c124a4804740988d61e5c115b9f6",
+       "layout": "IPY_MODEL_fde8329da0b24aff818eb65199ed223d",
+       "max": 30.0,
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+       "orientation": "horizontal",
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        "tabbable": null,
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-       "value": "number of examples processed for checking labels: 100%"
+       "value": 30.0
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@@ -4568,7 +4600,23 @@
        "width": null
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-     "faa337b288df409faa616d5854ec2c1d": {
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+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
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+       "_model_module_version": "2.0.0",
+       "_model_name": "ProgressStyleModel",
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+       "_view_module": "@jupyter-widgets/base",
+       "_view_module_version": "2.0.0",
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+     "fde8329da0b24aff818eb65199ed223d": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
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@@ -4621,22 +4669,30 @@
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-     "fdd5653325fc4ab5a8b567173af1df10": {
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-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_164675dd4f8f4cbf9a623e389dea6ec9",
+       "max": 30.0,
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diff --git a/master/.doctrees/nbsphinx/tutorials/tabular.ipynb b/master/.doctrees/nbsphinx/tutorials/tabular.ipynb
index c4bea62fc..7dce0276c 100644
--- a/master/.doctrees/nbsphinx/tutorials/tabular.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/tabular.ipynb
@@ -112,10 +112,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:42.691173Z",
-     "iopub.status.busy": "2024-02-13T00:42:42.690999Z",
-     "iopub.status.idle": "2024-02-13T00:42:43.895573Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.895028Z"
+     "iopub.execute_input": "2024-02-13T01:08:29.293945Z",
+     "iopub.status.busy": "2024-02-13T01:08:29.293768Z",
+     "iopub.status.idle": "2024-02-13T01:08:30.490030Z",
+     "shell.execute_reply": "2024-02-13T01:08:30.489507Z"
     },
     "nbsphinx": "hidden"
    },
@@ -125,7 +125,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -150,10 +150,10 @@
    "execution_count": 2,
    "metadata": {
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-     "iopub.status.idle": "2024-02-13T00:42:43.921287Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.920802Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.492829Z",
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     }
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    "outputs": [],
@@ -194,10 +194,10 @@
    "execution_count": 3,
    "metadata": {
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-     "iopub.status.idle": "2024-02-13T00:42:43.970211Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.969737Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.518838Z",
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+     "shell.execute_reply": "2024-02-13T01:08:30.650061Z"
     }
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    "outputs": [
@@ -304,10 +304,10 @@
    "execution_count": 4,
    "metadata": {
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-     "iopub.execute_input": "2024-02-13T00:42:43.972223Z",
-     "iopub.status.busy": "2024-02-13T00:42:43.971895Z",
-     "iopub.status.idle": "2024-02-13T00:42:43.975341Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.974896Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.652633Z",
+     "iopub.status.busy": "2024-02-13T01:08:30.652455Z",
+     "iopub.status.idle": "2024-02-13T01:08:30.656208Z",
+     "shell.execute_reply": "2024-02-13T01:08:30.655751Z"
     }
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    "outputs": [],
@@ -328,10 +328,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:43.977060Z",
-     "iopub.status.busy": "2024-02-13T00:42:43.976888Z",
-     "iopub.status.idle": "2024-02-13T00:42:43.985075Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.984666Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.658256Z",
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     }
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    "outputs": [],
@@ -383,10 +383,10 @@
    "execution_count": 6,
    "metadata": {
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-     "shell.execute_reply": "2024-02-13T00:42:43.988974Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.668421Z",
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@@ -408,10 +408,10 @@
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@@ -445,10 +445,10 @@
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-     "shell.execute_reply": "2024-02-13T00:42:46.184814Z"
+     "iopub.execute_input": "2024-02-13T01:08:31.204639Z",
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     }
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@@ -480,10 +480,10 @@
    "execution_count": 9,
    "metadata": {
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-     "shell.execute_reply": "2024-02-13T00:42:46.197181Z"
+     "iopub.execute_input": "2024-02-13T01:08:32.927748Z",
+     "iopub.status.busy": "2024-02-13T01:08:32.927142Z",
+     "iopub.status.idle": "2024-02-13T01:08:32.937409Z",
+     "shell.execute_reply": "2024-02-13T01:08:32.936870Z"
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    "outputs": [
@@ -604,10 +604,10 @@
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    "metadata": {
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-     "iopub.status.idle": "2024-02-13T00:42:46.203389Z",
-     "shell.execute_reply": "2024-02-13T00:42:46.202947Z"
+     "iopub.execute_input": "2024-02-13T01:08:32.939547Z",
+     "iopub.status.busy": "2024-02-13T01:08:32.939137Z",
+     "iopub.status.idle": "2024-02-13T01:08:32.943243Z",
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     }
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    "outputs": [],
@@ -632,10 +632,10 @@
    "execution_count": 11,
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-     "iopub.status.idle": "2024-02-13T00:42:46.212479Z",
-     "shell.execute_reply": "2024-02-13T00:42:46.212050Z"
+     "iopub.execute_input": "2024-02-13T01:08:32.945513Z",
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    "outputs": [],
@@ -657,10 +657,10 @@
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-     "shell.execute_reply": "2024-02-13T00:42:46.324327Z"
+     "iopub.execute_input": "2024-02-13T01:08:32.955090Z",
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@@ -690,10 +690,10 @@
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-     "shell.execute_reply": "2024-02-13T00:42:46.329164Z"
+     "iopub.execute_input": "2024-02-13T01:08:33.069839Z",
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+     "iopub.status.idle": "2024-02-13T01:08:33.072322Z",
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    "outputs": [],
@@ -714,10 +714,10 @@
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-     "iopub.status.idle": "2024-02-13T00:42:48.366698Z",
-     "shell.execute_reply": "2024-02-13T00:42:48.365922Z"
+     "iopub.execute_input": "2024-02-13T01:08:33.074205Z",
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     }
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@@ -737,10 +737,10 @@
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-     "shell.execute_reply": "2024-02-13T00:42:48.381371Z"
+     "iopub.execute_input": "2024-02-13T01:08:35.106336Z",
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+     "iopub.status.idle": "2024-02-13T01:08:35.117507Z",
+     "shell.execute_reply": "2024-02-13T01:08:35.117029Z"
     }
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    "outputs": [
@@ -770,10 +770,10 @@
    "execution_count": 16,
    "metadata": {
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-     "iopub.execute_input": "2024-02-13T00:42:48.384241Z",
-     "iopub.status.busy": "2024-02-13T00:42:48.383892Z",
-     "iopub.status.idle": "2024-02-13T00:42:48.415415Z",
-     "shell.execute_reply": "2024-02-13T00:42:48.414914Z"
+     "iopub.execute_input": "2024-02-13T01:08:35.119648Z",
+     "iopub.status.busy": "2024-02-13T01:08:35.119330Z",
+     "iopub.status.idle": "2024-02-13T01:08:35.175410Z",
+     "shell.execute_reply": "2024-02-13T01:08:35.174796Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/.doctrees/nbsphinx/tutorials/text.ipynb b/master/.doctrees/nbsphinx/tutorials/text.ipynb
index 18538d7df..3eb295acf 100644
--- a/master/.doctrees/nbsphinx/tutorials/text.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/text.ipynb
@@ -114,10 +114,10 @@
    "execution_count": 1,
    "metadata": {
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-     "iopub.execute_input": "2024-02-13T00:42:51.470844Z",
-     "iopub.status.busy": "2024-02-13T00:42:51.470633Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.260427Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.259865Z"
+     "iopub.execute_input": "2024-02-13T01:08:38.092425Z",
+     "iopub.status.busy": "2024-02-13T01:08:38.092254Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.805897Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.805327Z"
     },
     "nbsphinx": "hidden"
    },
@@ -134,7 +134,7 @@
     "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\"  # disable parallelism to avoid deadlocks with huggingface\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -159,10 +159,10 @@
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-     "iopub.status.busy": "2024-02-13T00:42:54.262566Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.265988Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.265540Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.808761Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.808186Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.811739Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.811146Z"
     }
    },
    "outputs": [],
@@ -184,10 +184,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.268097Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.267704Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.270840Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.270310Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.813751Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.813439Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.816553Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.816015Z"
     },
     "nbsphinx": "hidden"
    },
@@ -218,10 +218,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.272804Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.272618Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.315492Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.314934Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.818605Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.818269Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.868772Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.868239Z"
     }
    },
    "outputs": [
@@ -311,10 +311,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.317595Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.317320Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.320853Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.320398Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.871094Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.870690Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.874329Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.873872Z"
     }
    },
    "outputs": [],
@@ -329,10 +329,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.322935Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.322504Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.326062Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.325517Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.876570Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.876206Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.879535Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.878985Z"
     }
    },
    "outputs": [
@@ -341,7 +341,7 @@
      "output_type": "stream",
      "text": [
       "This dataset has 10 classes.\n",
-      "Classes: {'supported_cards_and_currencies', 'visa_or_mastercard', 'lost_or_stolen_phone', 'apple_pay_or_google_pay', 'getting_spare_card', 'cancel_transfer', 'card_payment_fee_charged', 'change_pin', 'beneficiary_not_allowed', 'card_about_to_expire'}\n"
+      "Classes: {'cancel_transfer', 'apple_pay_or_google_pay', 'change_pin', 'beneficiary_not_allowed', 'lost_or_stolen_phone', 'visa_or_mastercard', 'getting_spare_card', 'supported_cards_and_currencies', 'card_about_to_expire', 'card_payment_fee_charged'}\n"
      ]
     }
    ],
@@ -364,10 +364,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.328045Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.327855Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.331117Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.330553Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.881545Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.881247Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.884584Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.884114Z"
     }
    },
    "outputs": [
@@ -408,10 +408,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.333127Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.332818Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.336153Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.335666Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.886567Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.886294Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.889639Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.889197Z"
     }
    },
    "outputs": [],
@@ -452,10 +452,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.338029Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.337850Z",
-     "iopub.status.idle": "2024-02-13T00:42:58.199110Z",
-     "shell.execute_reply": "2024-02-13T00:42:58.198544Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.891643Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.891290Z",
+     "iopub.status.idle": "2024-02-13T01:08:44.750991Z",
+     "shell.execute_reply": "2024-02-13T01:08:44.750358Z"
     }
    },
    "outputs": [
@@ -510,10 +510,10 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:58.201714Z",
-     "iopub.status.busy": "2024-02-13T00:42:58.201490Z",
-     "iopub.status.idle": "2024-02-13T00:42:58.204798Z",
-     "shell.execute_reply": "2024-02-13T00:42:58.204395Z"
+     "iopub.execute_input": "2024-02-13T01:08:44.753844Z",
+     "iopub.status.busy": "2024-02-13T01:08:44.753504Z",
+     "iopub.status.idle": "2024-02-13T01:08:44.757581Z",
+     "shell.execute_reply": "2024-02-13T01:08:44.756535Z"
     }
    },
    "outputs": [],
@@ -535,10 +535,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:58.206779Z",
-     "iopub.status.busy": "2024-02-13T00:42:58.206469Z",
-     "iopub.status.idle": "2024-02-13T00:42:58.209088Z",
-     "shell.execute_reply": "2024-02-13T00:42:58.208664Z"
+     "iopub.execute_input": "2024-02-13T01:08:44.759591Z",
+     "iopub.status.busy": "2024-02-13T01:08:44.759291Z",
+     "iopub.status.idle": "2024-02-13T01:08:44.762187Z",
+     "shell.execute_reply": "2024-02-13T01:08:44.761741Z"
     }
    },
    "outputs": [],
@@ -553,10 +553,10 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:58.210925Z",
-     "iopub.status.busy": "2024-02-13T00:42:58.210753Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.504649Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.503987Z"
+     "iopub.execute_input": "2024-02-13T01:08:44.764186Z",
+     "iopub.status.busy": "2024-02-13T01:08:44.763860Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.070931Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.070245Z"
     },
     "scrolled": true
    },
@@ -579,10 +579,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.507863Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.507121Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.515183Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.514651Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.073800Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.073235Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.081363Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.080887Z"
     }
    },
    "outputs": [
@@ -683,10 +683,10 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.517502Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.517046Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.521338Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.520782Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.083578Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.083233Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.087478Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.086756Z"
     }
    },
    "outputs": [],
@@ -700,10 +700,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.523586Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.523250Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.526277Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.525748Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.089472Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.089153Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.092142Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.091597Z"
     }
    },
    "outputs": [
@@ -738,10 +738,10 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.528442Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.528108Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.531026Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.530560Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.094142Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.093964Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.096933Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.096350Z"
     }
    },
    "outputs": [],
@@ -761,10 +761,10 @@
    "execution_count": 17,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.532986Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.532662Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.540215Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.539751Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.099370Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.098865Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.107470Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.106936Z"
     }
    },
    "outputs": [
@@ -889,10 +889,10 @@
    "execution_count": 18,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.542231Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.542041Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.801720Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.801085Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.109868Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.109487Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.340849Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.340332Z"
     },
     "scrolled": true
    },
@@ -931,10 +931,10 @@
    "execution_count": 19,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.805178Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.804254Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.983042Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.982469Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.343564Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.343175Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.521216Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.520698Z"
     },
     "scrolled": true
    },
@@ -967,10 +967,10 @@
    "execution_count": 20,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.986898Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.985865Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.990975Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.990455Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.523754Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.523385Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.527063Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.526595Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/.doctrees/nbsphinx/tutorials/token_classification.ipynb b/master/.doctrees/nbsphinx/tutorials/token_classification.ipynb
index 9b2f4aa01..e96e1caaf 100644
--- a/master/.doctrees/nbsphinx/tutorials/token_classification.ipynb
+++ b/master/.doctrees/nbsphinx/tutorials/token_classification.ipynb
@@ -75,10 +75,10 @@
    "id": "ae8a08e0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:04.174708Z",
-     "iopub.status.busy": "2024-02-13T00:43:04.174530Z",
-     "iopub.status.idle": "2024-02-13T00:43:05.448184Z",
-     "shell.execute_reply": "2024-02-13T00:43:05.447435Z"
+     "iopub.execute_input": "2024-02-13T01:08:50.680983Z",
+     "iopub.status.busy": "2024-02-13T01:08:50.680568Z",
+     "iopub.status.idle": "2024-02-13T01:08:52.047522Z",
+     "shell.execute_reply": "2024-02-13T01:08:52.046779Z"
     }
    },
    "outputs": [
@@ -86,7 +86,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "--2024-02-13 00:43:04--  https://data.deepai.org/conll2003.zip\r\n",
+      "--2024-02-13 01:08:50--  https://data.deepai.org/conll2003.zip\r\n",
       "Resolving data.deepai.org (data.deepai.org)... "
      ]
     },
@@ -94,16 +94,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "169.150.236.97, 2400:52e0:1a00::1070:1\r\n",
-      "Connecting to data.deepai.org (data.deepai.org)|169.150.236.97|:443... connected.\r\n",
-      "HTTP request sent, awaiting response... "
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "200 OK\r\n",
+      "185.93.1.246, 2400:52e0:1a00::1069:1\r\n",
+      "Connecting to data.deepai.org (data.deepai.org)|185.93.1.246|:443... connected.\r\n",
+      "HTTP request sent, awaiting response... 200 OK\r\n",
       "Length: 982975 (960K) [application/zip]\r\n",
       "Saving to: ‘conll2003.zip’\r\n",
       "\r\n",
@@ -116,9 +109,9 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "conll2003.zip       100%[===================>] 959.94K  4.82MB/s    in 0.2s    \r\n",
+      "conll2003.zip       100%[===================>] 959.94K  --.-KB/s    in 0.1s    \r\n",
       "\r\n",
-      "2024-02-13 00:43:04 (4.82 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n",
+      "2024-02-13 01:08:51 (7.92 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n",
       "\r\n",
       "mkdir: cannot create directory ‘data’: File exists\r\n"
      ]
@@ -138,9 +131,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "--2024-02-13 00:43:05--  https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n",
-      "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 52.217.140.217, 52.217.108.172, 52.217.124.193, ...\r\n",
-      "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|52.217.140.217|:443... connected.\r\n",
+      "--2024-02-13 01:08:51--  https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n",
+      "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 52.217.82.132, 54.231.138.209, 3.5.28.120, ...\r\n",
+      "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|52.217.82.132|:443... connected.\r\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "HTTP request sent, awaiting response... "
      ]
     },
@@ -161,9 +160,17 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "pred_probs.npz      100%[===================>]  16.26M  89.6MB/s    in 0.2s    \r\n",
+      "pred_probs.npz       44%[=======>            ]   7.25M  36.3MB/s               "
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "pred_probs.npz      100%[===================>]  16.26M  60.7MB/s    in 0.3s    \r\n",
       "\r\n",
-      "2024-02-13 00:43:05 (89.6 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n",
+      "2024-02-13 01:08:51 (60.7 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n",
       "\r\n"
      ]
     }
@@ -180,10 +187,10 @@
    "id": "439b0305",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:05.451079Z",
-     "iopub.status.busy": "2024-02-13T00:43:05.450671Z",
-     "iopub.status.idle": "2024-02-13T00:43:06.564340Z",
-     "shell.execute_reply": "2024-02-13T00:43:06.563771Z"
+     "iopub.execute_input": "2024-02-13T01:08:52.050051Z",
+     "iopub.status.busy": "2024-02-13T01:08:52.049854Z",
+     "iopub.status.idle": "2024-02-13T01:08:53.131521Z",
+     "shell.execute_reply": "2024-02-13T01:08:53.130959Z"
     },
     "nbsphinx": "hidden"
    },
@@ -194,7 +201,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -220,10 +227,10 @@
    "id": "a1349304",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:06.566928Z",
-     "iopub.status.busy": "2024-02-13T00:43:06.566437Z",
-     "iopub.status.idle": "2024-02-13T00:43:06.570020Z",
-     "shell.execute_reply": "2024-02-13T00:43:06.569578Z"
+     "iopub.execute_input": "2024-02-13T01:08:53.134166Z",
+     "iopub.status.busy": "2024-02-13T01:08:53.133673Z",
+     "iopub.status.idle": "2024-02-13T01:08:53.137466Z",
+     "shell.execute_reply": "2024-02-13T01:08:53.137011Z"
     }
    },
    "outputs": [],
@@ -273,10 +280,10 @@
    "id": "ab9d59a0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:06.572045Z",
-     "iopub.status.busy": "2024-02-13T00:43:06.571766Z",
-     "iopub.status.idle": "2024-02-13T00:43:06.574735Z",
-     "shell.execute_reply": "2024-02-13T00:43:06.574279Z"
+     "iopub.execute_input": "2024-02-13T01:08:53.139517Z",
+     "iopub.status.busy": "2024-02-13T01:08:53.139169Z",
+     "iopub.status.idle": "2024-02-13T01:08:53.142016Z",
+     "shell.execute_reply": "2024-02-13T01:08:53.141597Z"
     },
     "nbsphinx": "hidden"
    },
@@ -294,10 +301,10 @@
    "id": "519cb80c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:06.576803Z",
-     "iopub.status.busy": "2024-02-13T00:43:06.576540Z",
-     "iopub.status.idle": "2024-02-13T00:43:15.738283Z",
-     "shell.execute_reply": "2024-02-13T00:43:15.737645Z"
+     "iopub.execute_input": "2024-02-13T01:08:53.143912Z",
+     "iopub.status.busy": "2024-02-13T01:08:53.143722Z",
+     "iopub.status.idle": "2024-02-13T01:09:02.179284Z",
+     "shell.execute_reply": "2024-02-13T01:09:02.178768Z"
     }
    },
    "outputs": [],
@@ -371,10 +378,10 @@
    "id": "202f1526",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:15.740962Z",
-     "iopub.status.busy": "2024-02-13T00:43:15.740620Z",
-     "iopub.status.idle": "2024-02-13T00:43:15.746062Z",
-     "shell.execute_reply": "2024-02-13T00:43:15.745601Z"
+     "iopub.execute_input": "2024-02-13T01:09:02.181744Z",
+     "iopub.status.busy": "2024-02-13T01:09:02.181477Z",
+     "iopub.status.idle": "2024-02-13T01:09:02.186852Z",
+     "shell.execute_reply": "2024-02-13T01:09:02.186427Z"
     },
     "nbsphinx": "hidden"
    },
@@ -414,10 +421,10 @@
    "id": "a4381f03",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:15.748134Z",
-     "iopub.status.busy": "2024-02-13T00:43:15.747800Z",
-     "iopub.status.idle": "2024-02-13T00:43:16.104300Z",
-     "shell.execute_reply": "2024-02-13T00:43:16.103644Z"
+     "iopub.execute_input": "2024-02-13T01:09:02.188840Z",
+     "iopub.status.busy": "2024-02-13T01:09:02.188513Z",
+     "iopub.status.idle": "2024-02-13T01:09:02.542148Z",
+     "shell.execute_reply": "2024-02-13T01:09:02.541571Z"
     }
    },
    "outputs": [],
@@ -454,10 +461,10 @@
    "id": "7842e4a3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:16.106794Z",
-     "iopub.status.busy": "2024-02-13T00:43:16.106584Z",
-     "iopub.status.idle": "2024-02-13T00:43:16.110882Z",
-     "shell.execute_reply": "2024-02-13T00:43:16.110338Z"
+     "iopub.execute_input": "2024-02-13T01:09:02.544756Z",
+     "iopub.status.busy": "2024-02-13T01:09:02.544358Z",
+     "iopub.status.idle": "2024-02-13T01:09:02.548740Z",
+     "shell.execute_reply": "2024-02-13T01:09:02.548281Z"
     }
    },
    "outputs": [
@@ -529,10 +536,10 @@
    "id": "2c2ad9ad",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:16.113016Z",
-     "iopub.status.busy": "2024-02-13T00:43:16.112696Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.488955Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.488232Z"
+     "iopub.execute_input": "2024-02-13T01:09:02.550853Z",
+     "iopub.status.busy": "2024-02-13T01:09:02.550545Z",
+     "iopub.status.idle": "2024-02-13T01:09:04.959158Z",
+     "shell.execute_reply": "2024-02-13T01:09:04.958496Z"
     }
    },
    "outputs": [],
@@ -554,10 +561,10 @@
    "id": "95dc7268",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.492127Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.491369Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.495211Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.494758Z"
+     "iopub.execute_input": "2024-02-13T01:09:04.962283Z",
+     "iopub.status.busy": "2024-02-13T01:09:04.961556Z",
+     "iopub.status.idle": "2024-02-13T01:09:04.965363Z",
+     "shell.execute_reply": "2024-02-13T01:09:04.964836Z"
     }
    },
    "outputs": [
@@ -593,10 +600,10 @@
    "id": "e13de188",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.497244Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.496929Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.502291Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.501828Z"
+     "iopub.execute_input": "2024-02-13T01:09:04.967363Z",
+     "iopub.status.busy": "2024-02-13T01:09:04.967026Z",
+     "iopub.status.idle": "2024-02-13T01:09:04.972235Z",
+     "shell.execute_reply": "2024-02-13T01:09:04.971776Z"
     }
    },
    "outputs": [
@@ -774,10 +781,10 @@
    "id": "e4a006bd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.504313Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.503980Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.529855Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.529371Z"
+     "iopub.execute_input": "2024-02-13T01:09:04.974307Z",
+     "iopub.status.busy": "2024-02-13T01:09:04.973987Z",
+     "iopub.status.idle": "2024-02-13T01:09:05.000776Z",
+     "shell.execute_reply": "2024-02-13T01:09:05.000183Z"
     }
    },
    "outputs": [
@@ -879,10 +886,10 @@
    "id": "c8f4e163",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.531957Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.531643Z",
-     "iopub.status.idle": "2024-02-13T00:43:18.536502Z",
-     "shell.execute_reply": "2024-02-13T00:43:18.535960Z"
+     "iopub.execute_input": "2024-02-13T01:09:05.003014Z",
+     "iopub.status.busy": "2024-02-13T01:09:05.002661Z",
+     "iopub.status.idle": "2024-02-13T01:09:05.007683Z",
+     "shell.execute_reply": "2024-02-13T01:09:05.007189Z"
     }
    },
    "outputs": [
@@ -956,10 +963,10 @@
    "id": "db0b5179",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:18.538559Z",
-     "iopub.status.busy": "2024-02-13T00:43:18.538225Z",
-     "iopub.status.idle": "2024-02-13T00:43:19.973837Z",
-     "shell.execute_reply": "2024-02-13T00:43:19.973279Z"
+     "iopub.execute_input": "2024-02-13T01:09:05.009826Z",
+     "iopub.status.busy": "2024-02-13T01:09:05.009504Z",
+     "iopub.status.idle": "2024-02-13T01:09:06.463987Z",
+     "shell.execute_reply": "2024-02-13T01:09:06.463485Z"
     }
    },
    "outputs": [
@@ -1131,10 +1138,10 @@
    "id": "a18795eb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:19.976037Z",
-     "iopub.status.busy": "2024-02-13T00:43:19.975689Z",
-     "iopub.status.idle": "2024-02-13T00:43:19.979882Z",
-     "shell.execute_reply": "2024-02-13T00:43:19.979346Z"
+     "iopub.execute_input": "2024-02-13T01:09:06.466176Z",
+     "iopub.status.busy": "2024-02-13T01:09:06.465836Z",
+     "iopub.status.idle": "2024-02-13T01:09:06.469775Z",
+     "shell.execute_reply": "2024-02-13T01:09:06.469321Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/.doctrees/tutorials/audio.doctree b/master/.doctrees/tutorials/audio.doctree
index ce085bb5161f75b8de97e6e712b491f35022f0e6..daf5c9a426fb01c8d1dee7470109db0cadaacc5a 100644
GIT binary patch
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diff --git a/master/.doctrees/tutorials/datalab/datalab_quickstart.doctree b/master/.doctrees/tutorials/datalab/datalab_quickstart.doctree
index d495bf991501c40cab8f708e41adcac6ad121323..987b4e43670d031d39a5ff7f6e7df5979acbcc2d 100644
GIT binary patch
delta 1308
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diff --git a/master/.doctrees/tutorials/datalab/index.doctree b/master/.doctrees/tutorials/datalab/index.doctree
index 85e0ec8261e1e0f8a651b786a38cbfb80e635a19..8c396b2faa7ee39c8e957fc1e2223f1f6dd4a184 100644
GIT binary patch
delta 62
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diff --git a/master/.doctrees/tutorials/datalab/text.doctree b/master/.doctrees/tutorials/datalab/text.doctree
index 842935e7eff1b71f9b1541e06d1cecd8b4166023..194024f4b0a174cc363016711fa159e267be8288 100644
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diff --git a/master/.doctrees/tutorials/dataset_health.doctree b/master/.doctrees/tutorials/dataset_health.doctree
index 88294fc50b5f1c57339c90b292caf3a0268c5e49..15bbb6c23e983c630ed5d799f0795e8f647dbff7 100644
GIT binary patch
delta 83
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delta 83
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diff --git a/master/.doctrees/tutorials/faq.doctree b/master/.doctrees/tutorials/faq.doctree
index 90c8c4082829d8a2121da732e86a15476a7d700d..0d2c8187f6399f1971803f0558801563186edc11 100644
GIT binary patch
delta 3887
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diff --git a/master/.doctrees/tutorials/indepth_overview.doctree b/master/.doctrees/tutorials/indepth_overview.doctree
index f05d3f433b2ec02f74461823d3db507c527632c3..0827b2ca758ef00e91e5d701dae2cae24db75724 100644
GIT binary patch
delta 3189
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diff --git a/master/.doctrees/tutorials/index.doctree b/master/.doctrees/tutorials/index.doctree
index 925c87ff630d5ff121ebad72ee7c80d7d4e89d2c..6ab652292fca9df7a064f1a70491928ab409d21a 100644
GIT binary patch
delta 62
zcmZ1=xj=G5AfsV?hG~9Qp=E}?X{upzl5tW>qJfENnz^B=X|jPqN|J?I|jtzS_4dXLR^Ro&qGxSYU4U?0MlTs25Oia_v4NXmx4GdC}EQ}0HjV(+q
cQj?4=O)ZU#OpKe~a<;$aWZeFilW8*_0B!6SEdT%j

delta 72
zcmZ3mkz>I|jtzS_4b$Q?vdk)rEcBBtk_}8vj4X^z(##Dl%}o+h4a|*FQjHVSEYmEE
c4HAuwlTA`h&CHtLa<;$aWZeFilW8*_0BS22c>n+a

diff --git a/master/.doctrees/tutorials/multilabel_classification.doctree b/master/.doctrees/tutorials/multilabel_classification.doctree
index e338ff1befbc03b7e2f675faab739add596f1995..4746f17dadd2a1d02106aba48965b9661e31d534 100644
GIT binary patch
delta 80
zcmeDE&)oZ;dBY`6+xQIA{H#LD41Lp7!{j96q?AMh6Vo(vLsQda1A~+#3nK$lV+&J@
k)Ffj|Q%fTw6J!09{N!T&;{4L02sbCbkW19PL4RO7@n%QOpP
kgG6KFWRp}=Gc)~^{N!T&;{4L0h($

diff --git a/master/.doctrees/tutorials/outliers.doctree b/master/.doctrees/tutorials/outliers.doctree
index 3ee87d1a6c3f40347e9c84427926ef27cecadc8d..4a8c6611e679c45d2cc5a005e8bc4ec5fbe91c4a 100644
GIT binary patch
delta 17248
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diff --git a/master/.doctrees/tutorials/pred_probs_cross_val.doctree b/master/.doctrees/tutorials/pred_probs_cross_val.doctree
index 13bc38df29ef4b43ef2bafdeafd91ee333a22524..7232a7b46bb30b93b7bd1373142751bd0b21bc76 100644
GIT binary patch
delta 64
zcmbQ&&N#1~af213VSI*ZepaDnhQ4X4VRDjjQc9wMiD{a-p{Z%Ifk8@=g^_`&v4yEc
TYLc;~sil#TiSg!aMq?)cgTWGN

delta 64
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TL87s7vPr6`nc3!SMq?)ceV`Jy

diff --git a/master/.doctrees/tutorials/regression.doctree b/master/.doctrees/tutorials/regression.doctree
index 394f3b3e030ed54d3c02ba4e80360d34d6645e53..1f6a9e53149c02a34e3cc7f01579b230f6724957 100644
GIT binary patch
delta 68
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YQj?4=O)ZU#OpKeKa&CXh$rv#k04rn`FaQ7m

delta 68
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diff --git a/master/.doctrees/tutorials/segmentation.doctree b/master/.doctrees/tutorials/segmentation.doctree
index d332ff87e6df742017f8a774b9cff74a4a17ccc5..28043bbccc80b8b333101b8ba270eed3d6547ff6 100644
GIT binary patch
delta 109923
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diff --git a/master/.doctrees/tutorials/text.doctree b/master/.doctrees/tutorials/text.doctree
index b512a600346a0bd1ad1eed90028236bbd18b6f53..0e2a3309c812fc413ba3cf9d78d0c90972c5a889 100644
GIT binary patch
delta 501
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delta 387
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delta 9571
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diff --git a/master/_modules/cleanlab/datalab/internal/report.html b/master/_modules/cleanlab/datalab/internal/report.html
index 24b19b43e..3c7624449 100644
--- a/master/_modules/cleanlab/datalab/internal/report.html
+++ b/master/_modules/cleanlab/datalab/internal/report.html
@@ -699,6 +699,10 @@ 
    Source code for cleanlab.datalab.internal.report
    
 
    
-
    
+
 
 
    
 
    
@@ -1474,7 +1474,7 @@ 
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diff --git a/master/tutorials/datalab/datalab_advanced.ipynb b/master/tutorials/datalab/datalab_advanced.ipynb
index 44aa6989b..4f2f3d7a1 100644
--- a/master/tutorials/datalab/datalab_advanced.ipynb
+++ b/master/tutorials/datalab/datalab_advanced.ipynb
@@ -80,10 +80,10 @@
    "execution_count": 1,
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-     "iopub.status.idle": "2024-02-13T00:32:04.175255Z",
-     "shell.execute_reply": "2024-02-13T00:32:04.174661Z"
+     "iopub.execute_input": "2024-02-13T00:57:07.765552Z",
+     "iopub.status.busy": "2024-02-13T00:57:07.765373Z",
+     "iopub.status.idle": "2024-02-13T00:57:08.901707Z",
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@@ -93,7 +93,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]  # TODO: make sure this list is updated\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -118,10 +118,10 @@
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@@ -252,10 +252,10 @@
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+     "iopub.execute_input": "2024-02-13T00:57:08.909068Z",
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@@ -353,10 +353,10 @@
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-     "shell.execute_reply": "2024-02-13T00:32:04.197493Z"
+     "iopub.execute_input": "2024-02-13T00:57:08.919362Z",
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@@ -445,10 +445,10 @@
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-     "shell.execute_reply": "2024-02-13T00:32:04.387212Z"
+     "iopub.execute_input": "2024-02-13T00:57:08.926106Z",
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@@ -517,10 +517,10 @@
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@@ -569,10 +569,10 @@
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@@ -608,10 +608,10 @@
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@@ -642,10 +642,10 @@
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@@ -709,10 +709,10 @@
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+     "iopub.execute_input": "2024-02-13T00:57:11.219770Z",
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@@ -821,10 +821,10 @@
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@@ -936,10 +936,10 @@
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@@ -1069,17 +1069,17 @@
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@@ -1115,10 +1115,10 @@
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@@ -1236,10 +1236,10 @@
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@@ -1296,10 +1296,10 @@
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+       "style": "IPY_MODEL_ae4e26f004604a569abe9a0b62e0d05c",
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+       "value": "Saving the dataset (1/1 shards): 100%"
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+        "IPY_MODEL_4596e9b62d184b00b7e50441cc8a7a8d",
+        "IPY_MODEL_90822746b9934cb9b08c8ded520b1300",
+        "IPY_MODEL_a10b6791af2d481682f6614e748b1fe3"
+       ],
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-       "layout": "IPY_MODEL_1e2d2887f06b4009819fa562671fe585",
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        "placeholder": "​",
-       "style": "IPY_MODEL_706b71cfad4945b1845c77184887981a",
+       "style": "IPY_MODEL_d27f3f8ddd2e4fff9ba56a4c400b1f03",
        "tabbable": null,
        "tooltip": null,
-       "value": "Saving the dataset (1/1 shards): 100%"
+       "value": " 132/132 [00:00<00:00, 12022.50 examples/s]"
       }
      },
-     "e9dabe1b0b1d4977bbd1fd74b2dedb53": {
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diff --git a/master/tutorials/datalab/datalab_quickstart.html b/master/tutorials/datalab/datalab_quickstart.html
index bf5d0557f..e72320d1d 100644
--- a/master/tutorials/datalab/datalab_quickstart.html
+++ b/master/tutorials/datalab/datalab_quickstart.html
@@ -899,14 +899,11 @@ 
    4. Use Datalab to find issues in the dataset
     Here is a summary of the different kinds of issues found in the data:
 
-           issue_type  num_issues
-                label          17
-              outlier           6
-       near_duplicate           4
-      class_imbalance           3
-                 null           0
-              non_iid           0
-underperforming_group           0
+     issue_type  num_issues
+          label          17
+        outlier           6
+ near_duplicate           4
+class_imbalance           3
 
 Dataset Information: num_examples: 132, num_classes: 4
 
diff --git a/master/tutorials/datalab/datalab_quickstart.ipynb b/master/tutorials/datalab/datalab_quickstart.ipynb
index de12dde96..ccbdfbaaa 100644
--- a/master/tutorials/datalab/datalab_quickstart.ipynb
+++ b/master/tutorials/datalab/datalab_quickstart.ipynb
@@ -78,10 +78,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:09.351379Z",
-     "iopub.status.busy": "2024-02-13T00:32:09.350969Z",
-     "iopub.status.idle": "2024-02-13T00:32:10.497590Z",
-     "shell.execute_reply": "2024-02-13T00:32:10.497091Z"
+     "iopub.execute_input": "2024-02-13T00:57:14.165662Z",
+     "iopub.status.busy": "2024-02-13T00:57:14.165261Z",
+     "iopub.status.idle": "2024-02-13T00:57:15.314470Z",
+     "shell.execute_reply": "2024-02-13T00:57:15.313815Z"
     },
     "nbsphinx": "hidden"
    },
@@ -91,7 +91,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]  # TODO: make sure this list is updated\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -116,10 +116,10 @@
    "execution_count": 2,
    "metadata": {
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-     "shell.execute_reply": "2024-02-13T00:32:10.502479Z"
+     "iopub.execute_input": "2024-02-13T00:57:15.317221Z",
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     }
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@@ -250,10 +250,10 @@
    "execution_count": 3,
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-     "shell.execute_reply": "2024-02-13T00:32:10.513013Z"
+     "iopub.execute_input": "2024-02-13T00:57:15.322214Z",
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     },
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@@ -356,10 +356,10 @@
    "execution_count": 4,
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-     "shell.execute_reply": "2024-02-13T00:32:10.519741Z"
+     "iopub.execute_input": "2024-02-13T00:57:15.333131Z",
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@@ -448,10 +448,10 @@
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-     "shell.execute_reply": "2024-02-13T00:32:10.710092Z"
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@@ -520,10 +520,10 @@
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-     "shell.execute_reply": "2024-02-13T00:32:11.079918Z"
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@@ -559,10 +559,10 @@
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@@ -602,10 +602,10 @@
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-     "shell.execute_reply": "2024-02-13T00:32:11.122342Z"
+     "iopub.execute_input": "2024-02-13T00:57:15.912658Z",
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     }
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@@ -647,10 +647,10 @@
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@@ -703,10 +703,10 @@
    "execution_count": 10,
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-     "iopub.execute_input": "2024-02-13T00:32:12.828987Z",
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-     "shell.execute_reply": "2024-02-13T00:32:12.844762Z"
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+     "shell.execute_reply": "2024-02-13T00:57:17.718974Z"
     }
    },
    "outputs": [
@@ -716,14 +716,11 @@
      "text": [
       "Here is a summary of the different kinds of issues found in the data:\n",
       "\n",
-      "           issue_type  num_issues\n",
-      "                label          17\n",
-      "              outlier           6\n",
-      "       near_duplicate           4\n",
-      "      class_imbalance           3\n",
-      "                 null           0\n",
-      "              non_iid           0\n",
-      "underperforming_group           0\n",
+      "     issue_type  num_issues\n",
+      "          label          17\n",
+      "        outlier           6\n",
+      " near_duplicate           4\n",
+      "class_imbalance           3\n",
       "\n",
       "Dataset Information: num_examples: 132, num_classes: 4\n",
       "\n",
@@ -837,10 +834,10 @@
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@@ -951,10 +948,10 @@
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@@ -1021,10 +1018,10 @@
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+     "iopub.status.busy": "2024-02-13T00:57:17.749387Z",
+     "iopub.status.idle": "2024-02-13T00:57:17.758117Z",
+     "shell.execute_reply": "2024-02-13T00:57:17.757568Z"
     }
    },
    "outputs": [
@@ -1335,10 +1332,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:12.885637Z",
-     "iopub.status.busy": "2024-02-13T00:32:12.885337Z",
-     "iopub.status.idle": "2024-02-13T00:32:12.892059Z",
-     "shell.execute_reply": "2024-02-13T00:32:12.891596Z"
+     "iopub.execute_input": "2024-02-13T00:57:17.760271Z",
+     "iopub.status.busy": "2024-02-13T00:57:17.759966Z",
+     "iopub.status.idle": "2024-02-13T00:57:17.766752Z",
+     "shell.execute_reply": "2024-02-13T00:57:17.766200Z"
     },
     "scrolled": true
    },
@@ -1463,10 +1460,10 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:12.894058Z",
-     "iopub.status.busy": "2024-02-13T00:32:12.893735Z",
-     "iopub.status.idle": "2024-02-13T00:32:12.902457Z",
-     "shell.execute_reply": "2024-02-13T00:32:12.901970Z"
+     "iopub.execute_input": "2024-02-13T00:57:17.768706Z",
+     "iopub.status.busy": "2024-02-13T00:57:17.768403Z",
+     "iopub.status.idle": "2024-02-13T00:57:17.777504Z",
+     "shell.execute_reply": "2024-02-13T00:57:17.776965Z"
     }
    },
    "outputs": [
diff --git a/master/tutorials/datalab/tabular.html b/master/tutorials/datalab/tabular.html
index 86a0c242f..92f375093 100644
--- a/master/tutorials/datalab/tabular.html
+++ b/master/tutorials/datalab/tabular.html
@@ -845,13 +845,11 @@ 
    5. Use cleanlab to find label issues
     Here is a summary of the different kinds of issues found in the data:
 
-           issue_type  num_issues
-                label         294
-              outlier          46
-       near_duplicate          17
-              non_iid           1
-      class_imbalance           0
-underperforming_group           0
+    issue_type  num_issues
+         label         294
+       outlier          46
+near_duplicate          17
+       non_iid           1
 
 Dataset Information: num_examples: 941, num_classes: 5
 
diff --git a/master/tutorials/datalab/tabular.ipynb b/master/tutorials/datalab/tabular.ipynb
index f89a75a9b..671a3fd35 100644
--- a/master/tutorials/datalab/tabular.ipynb
+++ b/master/tutorials/datalab/tabular.ipynb
@@ -74,10 +74,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:15.721460Z",
-     "iopub.status.busy": "2024-02-13T00:32:15.721277Z",
-     "iopub.status.idle": "2024-02-13T00:32:16.804642Z",
-     "shell.execute_reply": "2024-02-13T00:32:16.804046Z"
+     "iopub.execute_input": "2024-02-13T00:57:20.430293Z",
+     "iopub.status.busy": "2024-02-13T00:57:20.430100Z",
+     "iopub.status.idle": "2024-02-13T00:57:21.495197Z",
+     "shell.execute_reply": "2024-02-13T00:57:21.494634Z"
     },
     "nbsphinx": "hidden"
    },
@@ -87,7 +87,7 @@
     "dependencies = [\"cleanlab\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -112,10 +112,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:16.807330Z",
-     "iopub.status.busy": "2024-02-13T00:32:16.806889Z",
-     "iopub.status.idle": "2024-02-13T00:32:16.825709Z",
-     "shell.execute_reply": "2024-02-13T00:32:16.825289Z"
+     "iopub.execute_input": "2024-02-13T00:57:21.497947Z",
+     "iopub.status.busy": "2024-02-13T00:57:21.497490Z",
+     "iopub.status.idle": "2024-02-13T00:57:21.517182Z",
+     "shell.execute_reply": "2024-02-13T00:57:21.516696Z"
     }
    },
    "outputs": [],
@@ -155,10 +155,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:16.827757Z",
-     "iopub.status.busy": "2024-02-13T00:32:16.827490Z",
-     "iopub.status.idle": "2024-02-13T00:32:17.035317Z",
-     "shell.execute_reply": "2024-02-13T00:32:17.034751Z"
+     "iopub.execute_input": "2024-02-13T00:57:21.519151Z",
+     "iopub.status.busy": "2024-02-13T00:57:21.518890Z",
+     "iopub.status.idle": "2024-02-13T00:57:21.683904Z",
+     "shell.execute_reply": "2024-02-13T00:57:21.683335Z"
     }
    },
    "outputs": [
@@ -265,10 +265,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:17.037445Z",
-     "iopub.status.busy": "2024-02-13T00:32:17.037119Z",
-     "iopub.status.idle": "2024-02-13T00:32:17.040703Z",
-     "shell.execute_reply": "2024-02-13T00:32:17.040255Z"
+     "iopub.execute_input": "2024-02-13T00:57:21.685975Z",
+     "iopub.status.busy": "2024-02-13T00:57:21.685787Z",
+     "iopub.status.idle": "2024-02-13T00:57:21.689600Z",
+     "shell.execute_reply": "2024-02-13T00:57:21.689152Z"
     }
    },
    "outputs": [],
@@ -289,10 +289,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:17.042644Z",
-     "iopub.status.busy": "2024-02-13T00:32:17.042386Z",
-     "iopub.status.idle": "2024-02-13T00:32:17.049999Z",
-     "shell.execute_reply": "2024-02-13T00:32:17.049482Z"
+     "iopub.execute_input": "2024-02-13T00:57:21.691590Z",
+     "iopub.status.busy": "2024-02-13T00:57:21.691405Z",
+     "iopub.status.idle": "2024-02-13T00:57:21.698933Z",
+     "shell.execute_reply": "2024-02-13T00:57:21.698523Z"
     }
    },
    "outputs": [],
@@ -337,10 +337,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:17.052182Z",
-     "iopub.status.busy": "2024-02-13T00:32:17.051921Z",
-     "iopub.status.idle": "2024-02-13T00:32:17.054400Z",
-     "shell.execute_reply": "2024-02-13T00:32:17.053971Z"
+     "iopub.execute_input": "2024-02-13T00:57:21.701036Z",
+     "iopub.status.busy": "2024-02-13T00:57:21.700706Z",
+     "iopub.status.idle": "2024-02-13T00:57:21.703143Z",
+     "shell.execute_reply": "2024-02-13T00:57:21.702719Z"
     }
    },
    "outputs": [],
@@ -363,10 +363,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:17.056366Z",
-     "iopub.status.busy": "2024-02-13T00:32:17.056110Z",
-     "iopub.status.idle": "2024-02-13T00:32:20.126784Z",
-     "shell.execute_reply": "2024-02-13T00:32:20.126103Z"
+     "iopub.execute_input": "2024-02-13T00:57:21.705189Z",
+     "iopub.status.busy": "2024-02-13T00:57:21.704873Z",
+     "iopub.status.idle": "2024-02-13T00:57:24.641793Z",
+     "shell.execute_reply": "2024-02-13T00:57:24.641268Z"
     }
    },
    "outputs": [],
@@ -402,10 +402,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:20.129369Z",
-     "iopub.status.busy": "2024-02-13T00:32:20.129177Z",
-     "iopub.status.idle": "2024-02-13T00:32:20.139008Z",
-     "shell.execute_reply": "2024-02-13T00:32:20.138545Z"
+     "iopub.execute_input": "2024-02-13T00:57:24.644488Z",
+     "iopub.status.busy": "2024-02-13T00:57:24.644079Z",
+     "iopub.status.idle": "2024-02-13T00:57:24.654094Z",
+     "shell.execute_reply": "2024-02-13T00:57:24.653641Z"
     }
    },
    "outputs": [],
@@ -437,10 +437,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:20.141099Z",
-     "iopub.status.busy": "2024-02-13T00:32:20.140917Z",
-     "iopub.status.idle": "2024-02-13T00:32:21.993496Z",
-     "shell.execute_reply": "2024-02-13T00:32:21.992840Z"
+     "iopub.execute_input": "2024-02-13T00:57:24.656197Z",
+     "iopub.status.busy": "2024-02-13T00:57:24.656016Z",
+     "iopub.status.idle": "2024-02-13T00:57:26.506190Z",
+     "shell.execute_reply": "2024-02-13T00:57:26.505583Z"
     }
    },
    "outputs": [
@@ -477,10 +477,10 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:21.997354Z",
-     "iopub.status.busy": "2024-02-13T00:32:21.995885Z",
-     "iopub.status.idle": "2024-02-13T00:32:22.018652Z",
-     "shell.execute_reply": "2024-02-13T00:32:22.018135Z"
+     "iopub.execute_input": "2024-02-13T00:57:26.509996Z",
+     "iopub.status.busy": "2024-02-13T00:57:26.508710Z",
+     "iopub.status.idle": "2024-02-13T00:57:26.533221Z",
+     "shell.execute_reply": "2024-02-13T00:57:26.532725Z"
     },
     "scrolled": true
    },
@@ -491,13 +491,11 @@
      "text": [
       "Here is a summary of the different kinds of issues found in the data:\n",
       "\n",
-      "           issue_type  num_issues\n",
-      "                label         294\n",
-      "              outlier          46\n",
-      "       near_duplicate          17\n",
-      "              non_iid           1\n",
-      "      class_imbalance           0\n",
-      "underperforming_group           0\n",
+      "    issue_type  num_issues\n",
+      "         label         294\n",
+      "       outlier          46\n",
+      "near_duplicate          17\n",
+      "       non_iid           1\n",
       "\n",
       "Dataset Information: num_examples: 941, num_classes: 5\n",
       "\n",
@@ -607,10 +605,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:22.022280Z",
-     "iopub.status.busy": "2024-02-13T00:32:22.021375Z",
-     "iopub.status.idle": "2024-02-13T00:32:22.032683Z",
-     "shell.execute_reply": "2024-02-13T00:32:22.032197Z"
+     "iopub.execute_input": "2024-02-13T00:57:26.536756Z",
+     "iopub.status.busy": "2024-02-13T00:57:26.535851Z",
+     "iopub.status.idle": "2024-02-13T00:57:26.546857Z",
+     "shell.execute_reply": "2024-02-13T00:57:26.546373Z"
     }
    },
    "outputs": [
@@ -714,10 +712,10 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:22.036175Z",
-     "iopub.status.busy": "2024-02-13T00:32:22.035260Z",
-     "iopub.status.idle": "2024-02-13T00:32:22.048076Z",
-     "shell.execute_reply": "2024-02-13T00:32:22.047584Z"
+     "iopub.execute_input": "2024-02-13T00:57:26.550350Z",
+     "iopub.status.busy": "2024-02-13T00:57:26.549448Z",
+     "iopub.status.idle": "2024-02-13T00:57:26.563610Z",
+     "shell.execute_reply": "2024-02-13T00:57:26.563107Z"
     }
    },
    "outputs": [
@@ -846,10 +844,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:22.051608Z",
-     "iopub.status.busy": "2024-02-13T00:32:22.050689Z",
-     "iopub.status.idle": "2024-02-13T00:32:22.061953Z",
-     "shell.execute_reply": "2024-02-13T00:32:22.061460Z"
+     "iopub.execute_input": "2024-02-13T00:57:26.567092Z",
+     "iopub.status.busy": "2024-02-13T00:57:26.566179Z",
+     "iopub.status.idle": "2024-02-13T00:57:26.577057Z",
+     "shell.execute_reply": "2024-02-13T00:57:26.576662Z"
     }
    },
    "outputs": [
@@ -963,10 +961,10 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:22.064185Z",
-     "iopub.status.busy": "2024-02-13T00:32:22.063862Z",
-     "iopub.status.idle": "2024-02-13T00:32:22.072840Z",
-     "shell.execute_reply": "2024-02-13T00:32:22.072414Z"
+     "iopub.execute_input": "2024-02-13T00:57:26.579467Z",
+     "iopub.status.busy": "2024-02-13T00:57:26.579059Z",
+     "iopub.status.idle": "2024-02-13T00:57:26.588188Z",
+     "shell.execute_reply": "2024-02-13T00:57:26.587524Z"
     }
    },
    "outputs": [
@@ -1077,10 +1075,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:22.075086Z",
-     "iopub.status.busy": "2024-02-13T00:32:22.074619Z",
-     "iopub.status.idle": "2024-02-13T00:32:22.081235Z",
-     "shell.execute_reply": "2024-02-13T00:32:22.080788Z"
+     "iopub.execute_input": "2024-02-13T00:57:26.590264Z",
+     "iopub.status.busy": "2024-02-13T00:57:26.590086Z",
+     "iopub.status.idle": "2024-02-13T00:57:26.596978Z",
+     "shell.execute_reply": "2024-02-13T00:57:26.596416Z"
     }
    },
    "outputs": [
@@ -1164,10 +1162,10 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:22.083373Z",
-     "iopub.status.busy": "2024-02-13T00:32:22.083002Z",
-     "iopub.status.idle": "2024-02-13T00:32:22.089400Z",
-     "shell.execute_reply": "2024-02-13T00:32:22.088961Z"
+     "iopub.execute_input": "2024-02-13T00:57:26.599106Z",
+     "iopub.status.busy": "2024-02-13T00:57:26.598787Z",
+     "iopub.status.idle": "2024-02-13T00:57:26.605208Z",
+     "shell.execute_reply": "2024-02-13T00:57:26.604740Z"
     }
    },
    "outputs": [
@@ -1260,10 +1258,10 @@
    "execution_count": 17,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:22.091433Z",
-     "iopub.status.busy": "2024-02-13T00:32:22.091114Z",
-     "iopub.status.idle": "2024-02-13T00:32:22.097631Z",
-     "shell.execute_reply": "2024-02-13T00:32:22.097104Z"
+     "iopub.execute_input": "2024-02-13T00:57:26.607335Z",
+     "iopub.status.busy": "2024-02-13T00:57:26.606999Z",
+     "iopub.status.idle": "2024-02-13T00:57:26.613586Z",
+     "shell.execute_reply": "2024-02-13T00:57:26.613121Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/tutorials/datalab/text.html b/master/tutorials/datalab/text.html
index 9a6c65d0b..24f5d0805 100644
--- a/master/tutorials/datalab/text.html
+++ b/master/tutorials/datalab/text.html
@@ -707,7 +707,7 @@ 
    2. Load and format the text dataset
 
     This dataset has 10 classes.
-Classes: {'card_payment_fee_charged', 'change_pin', 'lost_or_stolen_phone', 'beneficiary_not_allowed', 'card_about_to_expire', 'getting_spare_card', 'apple_pay_or_google_pay', 'supported_cards_and_currencies', 'cancel_transfer', 'visa_or_mastercard'}
+Classes: {'supported_cards_and_currencies', 'visa_or_mastercard', 'getting_spare_card', 'card_about_to_expire', 'lost_or_stolen_phone', 'beneficiary_not_allowed', 'cancel_transfer', 'card_payment_fee_charged', 'apple_pay_or_google_pay', 'change_pin'}
 
    
 
    
 
    Let’s view the i-th example in the dataset:
    
@@ -754,43 +754,43 @@ 
    2. Load and format the text dataset
 
 
    
-
    
+
 
 
    
 
    
 
    
 
    
-
    
+
    
 
 
    
 
    
 
    
 
    
-
    
+
    
 
 
    
 
    
 
    
 
    
-
    
+
    
 
 
    
 
    
 
    
 
    
-
    
+
    
 
 
    
 
    
 
    
 
    
-
    
+
    
 
 
    
 
    
 
    
 
    
-
    
+
    
 
 
    
 
    
@@ -889,14 +889,11 @@ 
    4. Use cleanlab to find issues in your dataset
     Here is a summary of the different kinds of issues found in the data:
 
-           issue_type  num_issues
-                label          42
-              outlier          38
-       near_duplicate           4
-              non_iid           1
-                 null           0
-      class_imbalance           0
-underperforming_group           0
+    issue_type  num_issues
+         label          42
+       outlier          38
+near_duplicate           4
+       non_iid           1
 
 Dataset Information: num_examples: 1000, num_classes: 10
 
@@ -1526,7 +1523,7 @@ 
    Easy ModeCleanlab Studio which will automatically produce one for you. Super easy to use, Cleanlab Studio is no-code platform for data-centric AI that automatically: detects data
 issues (more types of issues than this cleanlab package), helps you quickly correct these data issues, confidently labels large subsets of an unlabeled dataset, and provides other smart metadata about each of your data points – all powered by a system that automatically trains/deploys the best ML model for your data. Try it for free!
    
 
 
 
diff --git a/master/tutorials/datalab/text.ipynb b/master/tutorials/datalab/text.ipynb
index fdbac61f8..1c38577a5 100644
--- a/master/tutorials/datalab/text.ipynb
+++ b/master/tutorials/datalab/text.ipynb
@@ -75,10 +75,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:24.618872Z",
-     "iopub.status.busy": "2024-02-13T00:32:24.618672Z",
-     "iopub.status.idle": "2024-02-13T00:32:27.512254Z",
-     "shell.execute_reply": "2024-02-13T00:32:27.511700Z"
+     "iopub.execute_input": "2024-02-13T00:57:29.286720Z",
+     "iopub.status.busy": "2024-02-13T00:57:29.286533Z",
+     "iopub.status.idle": "2024-02-13T00:57:32.182548Z",
+     "shell.execute_reply": "2024-02-13T00:57:32.181987Z"
     },
     "nbsphinx": "hidden"
    },
@@ -96,7 +96,7 @@
     "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\"  # disable parallelism to avoid deadlocks with huggingface\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -121,10 +121,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:27.514805Z",
-     "iopub.status.busy": "2024-02-13T00:32:27.514329Z",
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-     "shell.execute_reply": "2024-02-13T00:32:27.517126Z"
+     "iopub.execute_input": "2024-02-13T00:57:32.185293Z",
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+     "shell.execute_reply": "2024-02-13T00:57:32.187650Z"
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    "outputs": [],
@@ -145,10 +145,10 @@
    "execution_count": 3,
    "metadata": {
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-     "iopub.execute_input": "2024-02-13T00:32:27.519576Z",
-     "iopub.status.busy": "2024-02-13T00:32:27.519244Z",
-     "iopub.status.idle": "2024-02-13T00:32:27.522235Z",
-     "shell.execute_reply": "2024-02-13T00:32:27.521777Z"
+     "iopub.execute_input": "2024-02-13T00:57:32.190129Z",
+     "iopub.status.busy": "2024-02-13T00:57:32.189794Z",
+     "iopub.status.idle": "2024-02-13T00:57:32.192728Z",
+     "shell.execute_reply": "2024-02-13T00:57:32.192303Z"
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     "nbsphinx": "hidden"
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@@ -178,10 +178,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:27.524186Z",
-     "iopub.status.busy": "2024-02-13T00:32:27.524009Z",
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+     "iopub.execute_input": "2024-02-13T00:57:32.194775Z",
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+     "shell.execute_reply": "2024-02-13T00:57:32.245021Z"
     }
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    "outputs": [
@@ -271,10 +271,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:27.557125Z",
-     "iopub.status.busy": "2024-02-13T00:32:27.556723Z",
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-     "shell.execute_reply": "2024-02-13T00:32:27.560156Z"
+     "iopub.execute_input": "2024-02-13T00:57:32.247590Z",
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+     "shell.execute_reply": "2024-02-13T00:57:32.250745Z"
     }
    },
    "outputs": [
@@ -283,7 +283,7 @@
      "output_type": "stream",
      "text": [
       "This dataset has 10 classes.\n",
-      "Classes: {'card_payment_fee_charged', 'change_pin', 'lost_or_stolen_phone', 'beneficiary_not_allowed', 'card_about_to_expire', 'getting_spare_card', 'apple_pay_or_google_pay', 'supported_cards_and_currencies', 'cancel_transfer', 'visa_or_mastercard'}\n"
+      "Classes: {'supported_cards_and_currencies', 'visa_or_mastercard', 'getting_spare_card', 'card_about_to_expire', 'lost_or_stolen_phone', 'beneficiary_not_allowed', 'cancel_transfer', 'card_payment_fee_charged', 'apple_pay_or_google_pay', 'change_pin'}\n"
      ]
     }
    ],
@@ -307,10 +307,10 @@
    "execution_count": 6,
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-     "shell.execute_reply": "2024-02-13T00:32:27.565055Z"
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+     "shell.execute_reply": "2024-02-13T00:57:32.255580Z"
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    "outputs": [
@@ -365,17 +365,17 @@
    "execution_count": 7,
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-     "shell.execute_reply": "2024-02-13T00:32:31.966465Z"
+     "iopub.execute_input": "2024-02-13T00:57:32.258192Z",
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+     "shell.execute_reply": "2024-02-13T00:57:37.050794Z"
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     {
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@@ -389,7 +389,7 @@
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@@ -403,7 +403,7 @@
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@@ -417,7 +417,7 @@
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@@ -431,7 +431,7 @@
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@@ -445,7 +445,7 @@
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@@ -459,7 +459,7 @@
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@@ -522,10 +522,10 @@
    "execution_count": 8,
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-     "shell.execute_reply": "2024-02-13T00:32:32.828251Z"
+     "iopub.execute_input": "2024-02-13T00:57:37.053963Z",
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@@ -557,10 +557,10 @@
    "execution_count": 9,
    "metadata": {
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-     "shell.execute_reply": "2024-02-13T00:32:32.845291Z"
+     "iopub.execute_input": "2024-02-13T00:57:37.918246Z",
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+     "shell.execute_reply": "2024-02-13T00:57:37.920852Z"
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@@ -580,10 +580,10 @@
    "execution_count": 10,
    "metadata": {
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-     "iopub.execute_input": "2024-02-13T00:32:32.850114Z",
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-     "shell.execute_reply": "2024-02-13T00:32:34.441751Z"
+     "iopub.execute_input": "2024-02-13T00:57:37.924895Z",
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+     "shell.execute_reply": "2024-02-13T00:57:39.533007Z"
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@@ -628,10 +628,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:34.445441Z",
-     "iopub.status.busy": "2024-02-13T00:32:34.444663Z",
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-     "shell.execute_reply": "2024-02-13T00:32:34.464586Z"
+     "iopub.execute_input": "2024-02-13T00:57:39.537051Z",
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+     "shell.execute_reply": "2024-02-13T00:57:39.559337Z"
     },
     "scrolled": true
    },
@@ -642,14 +642,11 @@
      "text": [
       "Here is a summary of the different kinds of issues found in the data:\n",
       "\n",
-      "           issue_type  num_issues\n",
-      "                label          42\n",
-      "              outlier          38\n",
-      "       near_duplicate           4\n",
-      "              non_iid           1\n",
-      "                 null           0\n",
-      "      class_imbalance           0\n",
-      "underperforming_group           0\n",
+      "    issue_type  num_issues\n",
+      "         label          42\n",
+      "       outlier          38\n",
+      "near_duplicate           4\n",
+      "       non_iid           1\n",
       "\n",
       "Dataset Information: num_examples: 1000, num_classes: 10\n",
       "\n",
@@ -759,10 +756,10 @@
    "execution_count": 12,
    "metadata": {
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@@ -872,10 +869,10 @@
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-     "shell.execute_reply": "2024-02-13T00:32:34.482437Z"
+     "iopub.execute_input": "2024-02-13T00:57:39.574042Z",
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@@ -913,10 +910,10 @@
    "execution_count": 14,
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@@ -1033,10 +1030,10 @@
    "execution_count": 15,
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@@ -1119,10 +1116,10 @@
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@@ -1230,10 +1227,10 @@
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@@ -1344,10 +1341,10 @@
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@@ -1415,10 +1412,10 @@
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@@ -1497,10 +1494,10 @@
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@@ -1548,10 +1545,10 @@
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@@ -1601,7 +1598,7 @@
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@@ -1654,60 +1651,140 @@
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diff --git a/master/tutorials/dataset_health.ipynb b/master/tutorials/dataset_health.ipynb
index 5818938f5..f55f1f326 100644
--- a/master/tutorials/dataset_health.ipynb
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     "dependencies = [\"cleanlab\", \"requests\"]\n",
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-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
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diff --git a/master/tutorials/faq.html b/master/tutorials/faq.html
index 1a4fb5f2a..3a0ded7d8 100644
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@@ -701,13 +701,13 @@ 
    How can I find label issues in big datasets with limited memory?
 
    
 
    
-
    
+
    
 
 
    
 
    
 
    
 
    
-
    
+
    
 
 
    
 
    
@@ -1579,7 +1579,7 @@ 
    How to handle near-duplicate data identified by cleanlab?
 
    -/tmp/ipykernel_5790/1995098996.py:88: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.
+/tmp/ipykernel_5744/1995098996.py:88: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.
   to_keep_indices = duplicate_rows.groupby(group_key).apply(strategy_fn, **strategy_kwargs).explode().values
 
    
 
    
@@ -1621,7 +1621,7 @@ 
    Can’t find an answer to your question?new Github issue. Our developers may also provide personalized assistance in our Slack Community.
    
 
    Professional support and services are also available from our ML experts, learn more by emailing: info@cleanlab.ai
    
 
 
  
diff --git a/master/tutorials/faq.ipynb b/master/tutorials/faq.ipynb
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@@ -213,10 +213,10 @@
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@@ -238,10 +238,10 @@
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@@ -298,10 +298,10 @@
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@@ -315,7 +315,7 @@
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@@ -329,7 +329,7 @@
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@@ -421,10 +421,10 @@
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@@ -672,10 +672,10 @@
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@@ -761,10 +761,10 @@
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@@ -1206,7 +1206,7 @@
   },
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-   "id": "b55d1f15",
+   "id": "e403fc33",
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    "source": [
     "### How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?"
@@ -1214,7 +1214,7 @@
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-   "id": "f9c78075",
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     "When detecting underperforming groups in a dataset, Datalab provides the option for passing pre-computed\n",
@@ -1227,13 +1227,13 @@
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@@ -1274,7 +1274,7 @@
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-   "id": "079965f4",
+   "id": "10ab7d4d",
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     "For a tabular dataset, you can alternatively use a categorical column's values as cluster IDs:"
@@ -1283,13 +1283,13 @@
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-   "id": "34bfccad",
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    "source": [
     "### How to handle near-duplicate data identified by cleanlab?\n",
@@ -1336,13 +1336,13 @@
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@@ -1444,7 +1444,7 @@
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-   "id": "4aa28747",
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     "The functions above collect sets of near-duplicate examples. Within each\n",
@@ -1459,13 +1459,13 @@
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@@ -1482,7 +1482,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/tmp/ipykernel_5790/1995098996.py:88: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
+      "/tmp/ipykernel_5744/1995098996.py:88: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
       "  to_keep_indices = duplicate_rows.groupby(group_key).apply(strategy_fn, **strategy_kwargs).explode().values\n"
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@@ -1516,13 +1516,13 @@
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diff --git a/master/tutorials/image.html b/master/tutorials/image.html
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    2. Fetch and normalize the Fashion-MNIST dataset
 
 
    
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    [3]:
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 Computing feature embeddings ...
 
    
 
    
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    7. Use cleanlab to find issues
 
    
 
    
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+
 
 
    
 
    
@@ -2490,20 +2421,12 @@ 
    View report
     Here is a summary of the different kinds of issues found in the data:
 
-           issue_type  num_issues
-              outlier        3772
-                label        3585
-       near_duplicate         175
-      low_information         166
-                 dark          16
-                 null           0
-              non_iid           0
-      class_imbalance           0
-underperforming_group           0
-                light           0
-     odd_aspect_ratio           0
-             odd_size           0
-               blurry           0
+     issue_type  num_issues
+        outlier        3772
+          label        3585
+ near_duplicate         175
+low_information         166
+           dark          16
 
 Dataset Information: num_examples: 60000, num_classes: 10
 
@@ -3178,35 +3101,35 @@ 
    Dark images
       
-      dark_score
       is_dark_issue
+      dark_score
     
   
   
     
       34848
-      0.203922
       True
+      0.203922
     
     
       50270
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+      0.204588
     
     
       3936
-      0.213098
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+      0.213098
     
     
       733
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+      0.217686
     
     
       8094
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+      0.230118
     
   
 
@@ -3300,35 +3223,35 @@ 
    Low information images
     
       
-      low_information_score
       is_low_information_issue
+      low_information_score
     
   
   
     
       53050
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       True
+      0.067975
     
     
       40875
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+      0.089929
     
     
       9594
-      0.092601
       True
+      0.092601
     
     
       34825
-      0.107744
       True
+      0.107744
     
     
       37530
-      0.108516
       True
+      0.108516
     
   
 
@@ -3356,7 +3279,7 @@ 
    Easy ModeCleanlab Studio which will automatically produce one for you. Super easy to use, Cleanlab Studio is no-code platform for data-centric AI that automatically: detects data
 issues (more types of issues than this cleanlab package), helps you quickly correct these data issues, confidently labels large subsets of an unlabeled dataset, and provides other smart metadata about each of your data points – all powered by a system that automatically trains/deploys the best ML model for your data. Try it for free!
    
 
 
 
diff --git a/master/tutorials/image.ipynb b/master/tutorials/image.ipynb
index 407443a2c..fc0f9acc6 100644
--- a/master/tutorials/image.ipynb
+++ b/master/tutorials/image.ipynb
@@ -71,10 +71,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:55.756628Z",
-     "iopub.status.busy": "2024-02-13T00:32:55.756449Z",
-     "iopub.status.idle": "2024-02-13T00:32:58.578424Z",
-     "shell.execute_reply": "2024-02-13T00:32:58.577872Z"
+     "iopub.execute_input": "2024-02-13T00:58:00.754772Z",
+     "iopub.status.busy": "2024-02-13T00:58:00.754577Z",
+     "iopub.status.idle": "2024-02-13T00:58:03.694773Z",
+     "shell.execute_reply": "2024-02-13T00:58:03.694251Z"
     },
     "nbsphinx": "hidden"
    },
@@ -112,10 +112,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:58.580891Z",
-     "iopub.status.busy": "2024-02-13T00:32:58.580457Z",
-     "iopub.status.idle": "2024-02-13T00:32:58.583882Z",
-     "shell.execute_reply": "2024-02-13T00:32:58.583448Z"
+     "iopub.execute_input": "2024-02-13T00:58:03.697643Z",
+     "iopub.status.busy": "2024-02-13T00:58:03.697076Z",
+     "iopub.status.idle": "2024-02-13T00:58:03.700733Z",
+     "shell.execute_reply": "2024-02-13T00:58:03.700284Z"
     }
    },
    "outputs": [],
@@ -152,17 +152,17 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:32:58.585721Z",
-     "iopub.status.busy": "2024-02-13T00:32:58.585532Z",
-     "iopub.status.idle": "2024-02-13T00:33:00.315367Z",
-     "shell.execute_reply": "2024-02-13T00:33:00.314861Z"
+     "iopub.execute_input": "2024-02-13T00:58:03.703050Z",
+     "iopub.status.busy": "2024-02-13T00:58:03.702664Z",
+     "iopub.status.idle": "2024-02-13T00:58:05.979467Z",
+     "shell.execute_reply": "2024-02-13T00:58:05.978945Z"
     }
    },
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9eaa9f23d032404584b47b968c94bca7",
+       "model_id": "5e97d7a301904ec8a9e06bf177cb0f12",
        "version_major": 2,
        "version_minor": 0
       },
@@ -176,7 +176,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "824f70d558444a8fb4fa98914b32c2d7",
+       "model_id": "017960e634c04c6988dde5fbc57d815e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -190,7 +190,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9b5b8b9b315f43a9bc8737c0c5717292",
+       "model_id": "813e5ea418794e0ead8d5dc739fdd6ee",
        "version_major": 2,
        "version_minor": 0
       },
@@ -204,7 +204,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b7f47718d33d49b49194bfe156774feb",
+       "model_id": "0284a791f2dd45be979f1b9226c8f848",
        "version_major": 2,
        "version_minor": 0
       },
@@ -246,10 +246,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:33:00.317522Z",
-     "iopub.status.busy": "2024-02-13T00:33:00.317229Z",
-     "iopub.status.idle": "2024-02-13T00:33:00.321190Z",
-     "shell.execute_reply": "2024-02-13T00:33:00.320731Z"
+     "iopub.execute_input": "2024-02-13T00:58:05.981689Z",
+     "iopub.status.busy": "2024-02-13T00:58:05.981409Z",
+     "iopub.status.idle": "2024-02-13T00:58:05.985238Z",
+     "shell.execute_reply": "2024-02-13T00:58:05.984781Z"
     }
    },
    "outputs": [
@@ -274,17 +274,17 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:33:00.323196Z",
-     "iopub.status.busy": "2024-02-13T00:33:00.322914Z",
-     "iopub.status.idle": "2024-02-13T00:33:11.264666Z",
-     "shell.execute_reply": "2024-02-13T00:33:11.264026Z"
+     "iopub.execute_input": "2024-02-13T00:58:05.987152Z",
+     "iopub.status.busy": "2024-02-13T00:58:05.986879Z",
+     "iopub.status.idle": "2024-02-13T00:58:16.978518Z",
+     "shell.execute_reply": "2024-02-13T00:58:16.977984Z"
     }
    },
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9686a0ffbd234a7cb7be6bced38ad591",
+       "model_id": "c565faa2d0a14d12b39c26b4d8b090e7",
        "version_major": 2,
        "version_minor": 0
       },
@@ -322,10 +322,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:33:11.267275Z",
-     "iopub.status.busy": "2024-02-13T00:33:11.267045Z",
-     "iopub.status.idle": "2024-02-13T00:33:29.237710Z",
-     "shell.execute_reply": "2024-02-13T00:33:29.237105Z"
+     "iopub.execute_input": "2024-02-13T00:58:16.981250Z",
+     "iopub.status.busy": "2024-02-13T00:58:16.980869Z",
+     "iopub.status.idle": "2024-02-13T00:58:35.570043Z",
+     "shell.execute_reply": "2024-02-13T00:58:35.569496Z"
     }
    },
    "outputs": [],
@@ -358,10 +358,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:33:29.240507Z",
-     "iopub.status.busy": "2024-02-13T00:33:29.240101Z",
-     "iopub.status.idle": "2024-02-13T00:33:29.244824Z",
-     "shell.execute_reply": "2024-02-13T00:33:29.244401Z"
+     "iopub.execute_input": "2024-02-13T00:58:35.572770Z",
+     "iopub.status.busy": "2024-02-13T00:58:35.572389Z",
+     "iopub.status.idle": "2024-02-13T00:58:35.578304Z",
+     "shell.execute_reply": "2024-02-13T00:58:35.577847Z"
     }
    },
    "outputs": [],
@@ -399,10 +399,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:33:29.246630Z",
-     "iopub.status.busy": "2024-02-13T00:33:29.246452Z",
-     "iopub.status.idle": "2024-02-13T00:33:29.250375Z",
-     "shell.execute_reply": "2024-02-13T00:33:29.249866Z"
+     "iopub.execute_input": "2024-02-13T00:58:35.580167Z",
+     "iopub.status.busy": "2024-02-13T00:58:35.579866Z",
+     "iopub.status.idle": "2024-02-13T00:58:35.583840Z",
+     "shell.execute_reply": "2024-02-13T00:58:35.583329Z"
     },
     "nbsphinx": "hidden"
    },
@@ -539,10 +539,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:33:29.252505Z",
-     "iopub.status.busy": "2024-02-13T00:33:29.252330Z",
-     "iopub.status.idle": "2024-02-13T00:33:29.260794Z",
-     "shell.execute_reply": "2024-02-13T00:33:29.260382Z"
+     "iopub.execute_input": "2024-02-13T00:58:35.585854Z",
+     "iopub.status.busy": "2024-02-13T00:58:35.585564Z",
+     "iopub.status.idle": "2024-02-13T00:58:35.594411Z",
+     "shell.execute_reply": "2024-02-13T00:58:35.593839Z"
     },
     "nbsphinx": "hidden"
    },
@@ -667,10 +667,10 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:33:29.262611Z",
-     "iopub.status.busy": "2024-02-13T00:33:29.262441Z",
-     "iopub.status.idle": "2024-02-13T00:33:29.290079Z",
-     "shell.execute_reply": "2024-02-13T00:33:29.289625Z"
+     "iopub.execute_input": "2024-02-13T00:58:35.596468Z",
+     "iopub.status.busy": "2024-02-13T00:58:35.596151Z",
+     "iopub.status.idle": "2024-02-13T00:58:35.623359Z",
+     "shell.execute_reply": "2024-02-13T00:58:35.622709Z"
     }
    },
    "outputs": [],
@@ -707,10 +707,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:33:29.292158Z",
-     "iopub.status.busy": "2024-02-13T00:33:29.291894Z",
-     "iopub.status.idle": "2024-02-13T00:34:01.631526Z",
-     "shell.execute_reply": "2024-02-13T00:34:01.630773Z"
+     "iopub.execute_input": "2024-02-13T00:58:35.625991Z",
+     "iopub.status.busy": "2024-02-13T00:58:35.625671Z",
+     "iopub.status.idle": "2024-02-13T00:59:08.185564Z",
+     "shell.execute_reply": "2024-02-13T00:59:08.184818Z"
     }
    },
    "outputs": [
@@ -726,14 +726,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "epoch: 1 loss: 0.482 test acc: 86.720 time_taken: 4.760\n"
+      "epoch: 1 loss: 0.482 test acc: 86.720 time_taken: 4.837\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "epoch: 2 loss: 0.329 test acc: 88.195 time_taken: 4.454\n",
+      "epoch: 2 loss: 0.329 test acc: 88.195 time_taken: 4.654\n",
       "Computing feature embeddings ...\n"
      ]
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@@ -750,7 +750,7 @@
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+      " 40%|████      | 16/40 [00:00<00:00, 52.51it/s]"
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+      " 57%|█████▊    | 23/40 [00:00<00:00, 58.40it/s]"
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+      " 20%|██        | 8/40 [00:00<00:00, 39.02it/s]"
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-    {
-     "name": "stderr",
-     "output_type": "stream",
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+      "100%|██████████| 40/40 [00:00<00:00, 55.41it/s]"
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     {
@@ -906,14 +898,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "epoch: 1 loss: 0.493 test acc: 87.060 time_taken: 4.771\n"
+      "epoch: 1 loss: 0.493 test acc: 87.060 time_taken: 4.838\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "epoch: 2 loss: 0.330 test acc: 88.505 time_taken: 4.503\n",
+      "epoch: 2 loss: 0.330 test acc: 88.505 time_taken: 4.593\n",
       "Computing feature embeddings ...\n"
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      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "epoch: 1 loss: 0.476 test acc: 86.340 time_taken: 4.837\n"
+      "epoch: 1 loss: 0.476 test acc: 86.340 time_taken: 4.818\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "epoch: 2 loss: 0.328 test acc: 86.310 time_taken: 4.453\n",
+      "epoch: 2 loss: 0.328 test acc: 86.310 time_taken: 4.580\n",
       "Computing feature embeddings ...\n"
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+      "100%|██████████| 40/40 [00:00<00:00, 57.43it/s]"
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     {
@@ -1322,10 +1298,10 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:34:01.634066Z",
-     "iopub.status.busy": "2024-02-13T00:34:01.633674Z",
-     "iopub.status.idle": "2024-02-13T00:34:01.651297Z",
-     "shell.execute_reply": "2024-02-13T00:34:01.650763Z"
+     "iopub.execute_input": "2024-02-13T00:59:08.188354Z",
+     "iopub.status.busy": "2024-02-13T00:59:08.187953Z",
+     "iopub.status.idle": "2024-02-13T00:59:08.203040Z",
+     "shell.execute_reply": "2024-02-13T00:59:08.202573Z"
     }
    },
    "outputs": [],
@@ -1350,10 +1326,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:34:01.653598Z",
-     "iopub.status.busy": "2024-02-13T00:34:01.653409Z",
-     "iopub.status.idle": "2024-02-13T00:34:02.101998Z",
-     "shell.execute_reply": "2024-02-13T00:34:02.101435Z"
+     "iopub.execute_input": "2024-02-13T00:59:08.205177Z",
+     "iopub.status.busy": "2024-02-13T00:59:08.204907Z",
+     "iopub.status.idle": "2024-02-13T00:59:08.672404Z",
+     "shell.execute_reply": "2024-02-13T00:59:08.671787Z"
     }
    },
    "outputs": [],
@@ -1373,10 +1349,10 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:34:02.104501Z",
-     "iopub.status.busy": "2024-02-13T00:34:02.104157Z",
-     "iopub.status.idle": "2024-02-13T00:37:27.426886Z",
-     "shell.execute_reply": "2024-02-13T00:37:27.426223Z"
+     "iopub.execute_input": "2024-02-13T00:59:08.674848Z",
+     "iopub.status.busy": "2024-02-13T00:59:08.674501Z",
+     "iopub.status.idle": "2024-02-13T01:02:34.840489Z",
+     "shell.execute_reply": "2024-02-13T01:02:34.839806Z"
     }
    },
    "outputs": [
@@ -1422,7 +1398,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "222a7af54c8649df990267fdbbee1160",
+       "model_id": "e403d0a7480e4f9f92eb3272b2fa1116",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1461,10 +1437,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:27.429579Z",
-     "iopub.status.busy": "2024-02-13T00:37:27.428898Z",
-     "iopub.status.idle": "2024-02-13T00:37:28.111025Z",
-     "shell.execute_reply": "2024-02-13T00:37:28.110481Z"
+     "iopub.execute_input": "2024-02-13T01:02:34.843190Z",
+     "iopub.status.busy": "2024-02-13T01:02:34.842533Z",
+     "iopub.status.idle": "2024-02-13T01:02:35.549472Z",
+     "shell.execute_reply": "2024-02-13T01:02:35.548918Z"
     }
    },
    "outputs": [
@@ -1474,20 +1450,12 @@
      "text": [
       "Here is a summary of the different kinds of issues found in the data:\n",
       "\n",
-      "           issue_type  num_issues\n",
-      "              outlier        3772\n",
-      "                label        3585\n",
-      "       near_duplicate         175\n",
-      "      low_information         166\n",
-      "                 dark          16\n",
-      "                 null           0\n",
-      "              non_iid           0\n",
-      "      class_imbalance           0\n",
-      "underperforming_group           0\n",
-      "                light           0\n",
-      "     odd_aspect_ratio           0\n",
-      "             odd_size           0\n",
-      "               blurry           0\n",
+      "     issue_type  num_issues\n",
+      "        outlier        3772\n",
+      "          label        3585\n",
+      " near_duplicate         175\n",
+      "low_information         166\n",
+      "           dark          16\n",
       "\n",
       "Dataset Information: num_examples: 60000, num_classes: 10\n",
       "\n",
@@ -1613,10 +1581,10 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:28.113759Z",
-     "iopub.status.busy": "2024-02-13T00:37:28.113259Z",
-     "iopub.status.idle": "2024-02-13T00:37:28.174614Z",
-     "shell.execute_reply": "2024-02-13T00:37:28.174095Z"
+     "iopub.execute_input": "2024-02-13T01:02:35.552149Z",
+     "iopub.status.busy": "2024-02-13T01:02:35.551730Z",
+     "iopub.status.idle": "2024-02-13T01:02:35.613631Z",
+     "shell.execute_reply": "2024-02-13T01:02:35.613118Z"
     }
    },
    "outputs": [
@@ -1720,10 +1688,10 @@
    "execution_count": 17,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:28.176973Z",
-     "iopub.status.busy": "2024-02-13T00:37:28.176535Z",
-     "iopub.status.idle": "2024-02-13T00:37:28.184549Z",
-     "shell.execute_reply": "2024-02-13T00:37:28.184163Z"
+     "iopub.execute_input": "2024-02-13T01:02:35.615793Z",
+     "iopub.status.busy": "2024-02-13T01:02:35.615536Z",
+     "iopub.status.idle": "2024-02-13T01:02:35.624053Z",
+     "shell.execute_reply": "2024-02-13T01:02:35.623609Z"
     }
    },
    "outputs": [
@@ -1853,10 +1821,10 @@
    "execution_count": 18,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:28.186406Z",
-     "iopub.status.busy": "2024-02-13T00:37:28.186084Z",
-     "iopub.status.idle": "2024-02-13T00:37:28.190613Z",
-     "shell.execute_reply": "2024-02-13T00:37:28.190180Z"
+     "iopub.execute_input": "2024-02-13T01:02:35.626069Z",
+     "iopub.status.busy": "2024-02-13T01:02:35.625778Z",
+     "iopub.status.idle": "2024-02-13T01:02:35.630389Z",
+     "shell.execute_reply": "2024-02-13T01:02:35.629930Z"
     },
     "nbsphinx": "hidden"
    },
@@ -1902,10 +1870,10 @@
    "execution_count": 19,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:28.192727Z",
-     "iopub.status.busy": "2024-02-13T00:37:28.192307Z",
-     "iopub.status.idle": "2024-02-13T00:37:28.693460Z",
-     "shell.execute_reply": "2024-02-13T00:37:28.692943Z"
+     "iopub.execute_input": "2024-02-13T01:02:35.632341Z",
+     "iopub.status.busy": "2024-02-13T01:02:35.631985Z",
+     "iopub.status.idle": "2024-02-13T01:02:36.140502Z",
+     "shell.execute_reply": "2024-02-13T01:02:36.139929Z"
     }
    },
    "outputs": [
@@ -1940,10 +1908,10 @@
    "execution_count": 20,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:28.695669Z",
-     "iopub.status.busy": "2024-02-13T00:37:28.695328Z",
-     "iopub.status.idle": "2024-02-13T00:37:28.703541Z",
-     "shell.execute_reply": "2024-02-13T00:37:28.702996Z"
+     "iopub.execute_input": "2024-02-13T01:02:36.142829Z",
+     "iopub.status.busy": "2024-02-13T01:02:36.142489Z",
+     "iopub.status.idle": "2024-02-13T01:02:36.151064Z",
+     "shell.execute_reply": "2024-02-13T01:02:36.150522Z"
     }
    },
    "outputs": [
@@ -2110,10 +2078,10 @@
    "execution_count": 21,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:28.705905Z",
-     "iopub.status.busy": "2024-02-13T00:37:28.705575Z",
-     "iopub.status.idle": "2024-02-13T00:37:28.712683Z",
-     "shell.execute_reply": "2024-02-13T00:37:28.712224Z"
+     "iopub.execute_input": "2024-02-13T01:02:36.153978Z",
+     "iopub.status.busy": "2024-02-13T01:02:36.153514Z",
+     "iopub.status.idle": "2024-02-13T01:02:36.160812Z",
+     "shell.execute_reply": "2024-02-13T01:02:36.160340Z"
     },
     "nbsphinx": "hidden"
    },
@@ -2189,10 +2157,10 @@
    "execution_count": 22,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:28.714603Z",
-     "iopub.status.busy": "2024-02-13T00:37:28.714268Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.177399Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.176813Z"
+     "iopub.execute_input": "2024-02-13T01:02:36.162926Z",
+     "iopub.status.busy": "2024-02-13T01:02:36.162622Z",
+     "iopub.status.idle": "2024-02-13T01:02:36.642302Z",
+     "shell.execute_reply": "2024-02-13T01:02:36.641688Z"
     }
    },
    "outputs": [
@@ -2229,10 +2197,10 @@
    "execution_count": 23,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.179744Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.179408Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.194527Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.194058Z"
+     "iopub.execute_input": "2024-02-13T01:02:36.644566Z",
+     "iopub.status.busy": "2024-02-13T01:02:36.644228Z",
+     "iopub.status.idle": "2024-02-13T01:02:36.659948Z",
+     "shell.execute_reply": "2024-02-13T01:02:36.659444Z"
     }
    },
    "outputs": [
@@ -2389,10 +2357,10 @@
    "execution_count": 24,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.196641Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.196309Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.201682Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.201263Z"
+     "iopub.execute_input": "2024-02-13T01:02:36.662210Z",
+     "iopub.status.busy": "2024-02-13T01:02:36.661895Z",
+     "iopub.status.idle": "2024-02-13T01:02:36.667499Z",
+     "shell.execute_reply": "2024-02-13T01:02:36.667024Z"
     },
     "nbsphinx": "hidden"
    },
@@ -2437,10 +2405,10 @@
    "execution_count": 25,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.203671Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.203358Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.663858Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.663286Z"
+     "iopub.execute_input": "2024-02-13T01:02:36.669469Z",
+     "iopub.status.busy": "2024-02-13T01:02:36.669147Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.140776Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.140223Z"
     }
    },
    "outputs": [
@@ -2522,10 +2490,10 @@
    "execution_count": 26,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.666379Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.666181Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.675842Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.675332Z"
+     "iopub.execute_input": "2024-02-13T01:02:37.143358Z",
+     "iopub.status.busy": "2024-02-13T01:02:37.143134Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.153301Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.152783Z"
     }
    },
    "outputs": [
@@ -2550,47 +2518,47 @@
        "  \n",
        "    \n",
        "      \n",
-       "      dark_score\n",
        "      is_dark_issue\n",
+       "      dark_score\n",
        "    \n",
        "  \n",
        "  \n",
        "    \n",
        "      34848\n",
-       "      0.203922\n",
        "      True\n",
+       "      0.203922\n",
        "    \n",
        "    \n",
        "      50270\n",
-       "      0.204588\n",
        "      True\n",
+       "      0.204588\n",
        "    \n",
        "    \n",
        "      3936\n",
-       "      0.213098\n",
        "      True\n",
+       "      0.213098\n",
        "    \n",
        "    \n",
        "      733\n",
-       "      0.217686\n",
        "      True\n",
+       "      0.217686\n",
        "    \n",
        "    \n",
        "      8094\n",
-       "      0.230118\n",
        "      True\n",
+       "      0.230118\n",
        "    \n",
        "  \n",
        "\n",
        "
    "
       ],
       "text/plain": [
-       "       dark_score  is_dark_issue\n",
-       "34848    0.203922           True\n",
-       "50270    0.204588           True\n",
-       "3936     0.213098           True\n",
-       "733      0.217686           True\n",
-       "8094     0.230118           True"
+       "       is_dark_issue  dark_score\n",
+       "34848           True    0.203922\n",
+       "50270           True    0.204588\n",
+       "3936            True    0.213098\n",
+       "733             True    0.217686\n",
+       "8094            True    0.230118"
       ]
      },
      "execution_count": 26,
@@ -2653,10 +2621,10 @@
    "execution_count": 27,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.678176Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.677985Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.683662Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.683103Z"
+     "iopub.execute_input": "2024-02-13T01:02:37.155873Z",
+     "iopub.status.busy": "2024-02-13T01:02:37.155666Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.162357Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.161820Z"
     },
     "nbsphinx": "hidden"
    },
@@ -2693,10 +2661,10 @@
    "execution_count": 28,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.685941Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.685751Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.889426Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.888952Z"
+     "iopub.execute_input": "2024-02-13T01:02:37.164598Z",
+     "iopub.status.busy": "2024-02-13T01:02:37.164401Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.368662Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.368171Z"
     }
    },
    "outputs": [
@@ -2738,10 +2706,10 @@
    "execution_count": 29,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.891637Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.891305Z",
-     "iopub.status.idle": "2024-02-13T00:37:29.899394Z",
-     "shell.execute_reply": "2024-02-13T00:37:29.898837Z"
+     "iopub.execute_input": "2024-02-13T01:02:37.370798Z",
+     "iopub.status.busy": "2024-02-13T01:02:37.370458Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.378223Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.377660Z"
     }
    },
    "outputs": [
@@ -2766,47 +2734,47 @@
        "  \n",
        "    \n",
        "      \n",
-       "      low_information_score\n",
        "      is_low_information_issue\n",
+       "      low_information_score\n",
        "    \n",
        "  \n",
        "  \n",
        "    \n",
        "      53050\n",
-       "      0.067975\n",
        "      True\n",
+       "      0.067975\n",
        "    \n",
        "    \n",
        "      40875\n",
-       "      0.089929\n",
        "      True\n",
+       "      0.089929\n",
        "    \n",
        "    \n",
        "      9594\n",
-       "      0.092601\n",
        "      True\n",
+       "      0.092601\n",
        "    \n",
        "    \n",
        "      34825\n",
-       "      0.107744\n",
        "      True\n",
+       "      0.107744\n",
        "    \n",
        "    \n",
        "      37530\n",
-       "      0.108516\n",
        "      True\n",
+       "      0.108516\n",
        "    \n",
        "  \n",
        "\n",
        "
    "
       ],
       "text/plain": [
-       "       low_information_score  is_low_information_issue\n",
-       "53050               0.067975                      True\n",
-       "40875               0.089929                      True\n",
-       "9594                0.092601                      True\n",
-       "34825               0.107744                      True\n",
-       "37530               0.108516                      True"
+       "       is_low_information_issue  low_information_score\n",
+       "53050                      True               0.067975\n",
+       "40875                      True               0.089929\n",
+       "9594                       True               0.092601\n",
+       "34825                      True               0.107744\n",
+       "37530                      True               0.108516"
       ]
      },
      "execution_count": 29,
@@ -2827,10 +2795,10 @@
    "execution_count": 30,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:29.901327Z",
-     "iopub.status.busy": "2024-02-13T00:37:29.900995Z",
-     "iopub.status.idle": "2024-02-13T00:37:30.094897Z",
-     "shell.execute_reply": "2024-02-13T00:37:30.094353Z"
+     "iopub.execute_input": "2024-02-13T01:02:37.380209Z",
+     "iopub.status.busy": "2024-02-13T01:02:37.380029Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.576496Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.575996Z"
     }
    },
    "outputs": [
@@ -2870,10 +2838,10 @@
    "execution_count": 31,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:30.097178Z",
-     "iopub.status.busy": "2024-02-13T00:37:30.096845Z",
-     "iopub.status.idle": "2024-02-13T00:37:30.101066Z",
-     "shell.execute_reply": "2024-02-13T00:37:30.100641Z"
+     "iopub.execute_input": "2024-02-13T01:02:37.578759Z",
+     "iopub.status.busy": "2024-02-13T01:02:37.578414Z",
+     "iopub.status.idle": "2024-02-13T01:02:37.582664Z",
+     "shell.execute_reply": "2024-02-13T01:02:37.582233Z"
     },
     "nbsphinx": "hidden"
    },
@@ -2910,7 +2878,7 @@
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {
     "state": {
-     "00808d5dc47d421fa85dfba0084f6c14": {
+     "0150faad00cf4b0fa5003bd89bc6c035": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
       "model_name": "HTMLStyleModel",
@@ -2928,25 +2896,81 @@
        "text_color": null
       }
      },
-     "09ac7217cdac4f0090621b6aa6e249c9": {
+     "017960e634c04c6988dde5fbc57d815e": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
+      "model_name": "HBoxModel",
       "state": {
+       "_dom_classes": [],
        "_model_module": "@jupyter-widgets/controls",
        "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
+       "_model_name": "HBoxModel",
        "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
+       "_view_module": "@jupyter-widgets/controls",
        "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_b780b4fd2801474280ad84e713b25fb6",
+        "IPY_MODEL_abf91823558a430bbf6531d6199c83a6",
+        "IPY_MODEL_c44a3a846d79432e952ba641d52e33da"
+       ],
+       "layout": "IPY_MODEL_ea5f6403c8df4b90a9e3b07052e6aab2",
+       "tabbable": null,
+       "tooltip": null
+      }
+     },
+     "0284a791f2dd45be979f1b9226c8f848": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "HBoxModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HBoxView",
+       "box_style": "",
+       "children": [
+        "IPY_MODEL_ae88b8d5236542e18913a118fcf5f605",
+        "IPY_MODEL_09a69051582d4b2389b2afc3732e9c8f",
+        "IPY_MODEL_af52b95ed6354bd7a734942e3a64d975"
+       ],
+       "layout": "IPY_MODEL_b4989e9b88c54b5b8bd25e12894d3fdb",
+       "tabbable": null,
+       "tooltip": null
+      }
+     },
+     "09a69051582d4b2389b2afc3732e9c8f": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "FloatProgressModel",
+      "state": {
+       "_dom_classes": [],
+       "_model_module": "@jupyter-widgets/controls",
+       "_model_module_version": "2.0.0",
+       "_model_name": "FloatProgressModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_f1266d99ab1e4818866e8aed409423f7",
+       "max": 10000.0,
+       "min": 0.0,
+       "orientation": "horizontal",
+       "style": "IPY_MODEL_83ce5d03962d495694880128ff446cee",
+       "tabbable": null,
+       "tooltip": null,
+       "value": 10000.0
       }
      },
-     "0c7df9b73cd548b099cdcf0e0fb5df9f": {
+     "0bb76ba717d44652ba27a4c3713e71c5": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -2999,7 +3023,61 @@
        "width": null
       }
      },
-     "0e1c112aee9741da94938519f347530d": {
+     "0f4fcc0d5a6343069f27cdfe86c9e495": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
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diff --git a/master/tutorials/indepth_overview.html b/master/tutorials/indepth_overview.html
index 8c2624ce7..c2ebfbcd8 100644
--- a/master/tutorials/indepth_overview.html
+++ b/master/tutorials/indepth_overview.html
@@ -799,14 +799,11 @@ 
    Workflow 1: Use Datalab to detect many types of issues
     Here is a summary of the different kinds of issues found in the data:
 
-           issue_type  num_issues
-                label          64
-              outlier           7
-       near_duplicate           6
-              non_iid           1
-                 null           0
-      class_imbalance           0
-underperforming_group           0
+    issue_type  num_issues
+         label          64
+       outlier           7
+near_duplicate           6
+       non_iid           1
 
 Dataset Information: num_examples: 250, num_classes: 4
 
diff --git a/master/tutorials/indepth_overview.ipynb b/master/tutorials/indepth_overview.ipynb
index 880e905a4..e3aa13e3e 100644
--- a/master/tutorials/indepth_overview.ipynb
+++ b/master/tutorials/indepth_overview.ipynb
@@ -53,10 +53,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
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@@ -68,7 +68,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -95,10 +95,10 @@
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@@ -234,10 +234,10 @@
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@@ -340,10 +340,10 @@
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@@ -393,10 +393,10 @@
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@@ -428,10 +428,10 @@
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@@ -475,10 +475,10 @@
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@@ -489,14 +489,11 @@
      "text": [
       "Here is a summary of the different kinds of issues found in the data:\n",
       "\n",
-      "           issue_type  num_issues\n",
-      "                label          64\n",
-      "              outlier           7\n",
-      "       near_duplicate           6\n",
-      "              non_iid           1\n",
-      "                 null           0\n",
-      "      class_imbalance           0\n",
-      "underperforming_group           0\n",
+      "    issue_type  num_issues\n",
+      "         label          64\n",
+      "       outlier           7\n",
+      "near_duplicate           6\n",
+      "       non_iid           1\n",
       "\n",
       "Dataset Information: num_examples: 250, num_classes: 4\n",
       "\n",
@@ -606,10 +603,10 @@
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@@ -728,10 +725,10 @@
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@@ -780,10 +777,10 @@
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@@ -890,10 +887,10 @@
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@@ -930,10 +927,10 @@
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@@ -1399,10 +1396,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.279222Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.278903Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.288296Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.287868Z"
+     "iopub.execute_input": "2024-02-13T01:02:46.981879Z",
+     "iopub.status.busy": "2024-02-13T01:02:46.981516Z",
+     "iopub.status.idle": "2024-02-13T01:02:46.991691Z",
+     "shell.execute_reply": "2024-02-13T01:02:46.991205Z"
     },
     "id": "0lonvOYvjruV"
    },
@@ -1549,10 +1546,10 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.290394Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.290070Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.375577Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.374951Z"
+     "iopub.execute_input": "2024-02-13T01:02:46.993796Z",
+     "iopub.status.busy": "2024-02-13T01:02:46.993525Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.086416Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.085763Z"
     },
     "id": "MfqTCa3kjruV"
    },
@@ -1633,10 +1630,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.377920Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.377692Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.499197Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.498547Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.089076Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.088611Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.215679Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.214901Z"
     },
     "id": "9ZtWAYXqMAPL"
    },
@@ -1696,10 +1693,10 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.501539Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.501332Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.505424Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.504936Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.217945Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.217649Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.221440Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.220898Z"
     },
     "id": "0rXP3ZPWjruW"
    },
@@ -1737,10 +1734,10 @@
    "execution_count": 17,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.507408Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.507232Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.510931Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.510362Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.223439Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.223109Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.226899Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.226348Z"
     },
     "id": "-iRPe8KXjruW"
    },
@@ -1795,10 +1792,10 @@
    "execution_count": 18,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.513248Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.512859Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.553205Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.552731Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.228890Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.228567Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.266132Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.265631Z"
     },
     "id": "ZpipUliyjruW"
    },
@@ -1849,10 +1846,10 @@
    "execution_count": 19,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.555251Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.554920Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.597110Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.596642Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.268385Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.268026Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.310970Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.310465Z"
     },
     "id": "SLq-3q4xjruX"
    },
@@ -1921,10 +1918,10 @@
    "execution_count": 20,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.599076Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.598758Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.690060Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.689493Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.313091Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.312775Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.407546Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.406889Z"
     },
     "id": "g5LHhhuqFbXK"
    },
@@ -1956,10 +1953,10 @@
    "execution_count": 21,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.692611Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.692367Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.771815Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.771177Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.410185Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.409818Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.502742Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.502159Z"
     },
     "id": "p7w8F8ezBcet"
    },
@@ -2016,10 +2013,10 @@
    "execution_count": 22,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.774187Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.773955Z",
-     "iopub.status.idle": "2024-02-13T00:37:39.984108Z",
-     "shell.execute_reply": "2024-02-13T00:37:39.983487Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.504966Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.504681Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.719273Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.718779Z"
     },
     "id": "WETRL74tE_sU"
    },
@@ -2054,10 +2051,10 @@
    "execution_count": 23,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:39.986424Z",
-     "iopub.status.busy": "2024-02-13T00:37:39.986016Z",
-     "iopub.status.idle": "2024-02-13T00:37:40.152086Z",
-     "shell.execute_reply": "2024-02-13T00:37:40.151450Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.721525Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.721161Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.914563Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.913919Z"
     },
     "id": "kCfdx2gOLmXS"
    },
@@ -2219,10 +2216,10 @@
    "execution_count": 24,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:40.154261Z",
-     "iopub.status.busy": "2024-02-13T00:37:40.154028Z",
-     "iopub.status.idle": "2024-02-13T00:37:40.160333Z",
-     "shell.execute_reply": "2024-02-13T00:37:40.159779Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.917096Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.916711Z",
+     "iopub.status.idle": "2024-02-13T01:02:47.922691Z",
+     "shell.execute_reply": "2024-02-13T01:02:47.922142Z"
     },
     "id": "-uogYRWFYnuu"
    },
@@ -2276,10 +2273,10 @@
    "execution_count": 25,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:40.162300Z",
-     "iopub.status.busy": "2024-02-13T00:37:40.161998Z",
-     "iopub.status.idle": "2024-02-13T00:37:40.381020Z",
-     "shell.execute_reply": "2024-02-13T00:37:40.380421Z"
+     "iopub.execute_input": "2024-02-13T01:02:47.924839Z",
+     "iopub.status.busy": "2024-02-13T01:02:47.924517Z",
+     "iopub.status.idle": "2024-02-13T01:02:48.145432Z",
+     "shell.execute_reply": "2024-02-13T01:02:48.144840Z"
     },
     "id": "pG-ljrmcYp9Q"
    },
@@ -2326,10 +2323,10 @@
    "execution_count": 26,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:40.383322Z",
-     "iopub.status.busy": "2024-02-13T00:37:40.383000Z",
-     "iopub.status.idle": "2024-02-13T00:37:41.471029Z",
-     "shell.execute_reply": "2024-02-13T00:37:41.470469Z"
+     "iopub.execute_input": "2024-02-13T01:02:48.147699Z",
+     "iopub.status.busy": "2024-02-13T01:02:48.147291Z",
+     "iopub.status.idle": "2024-02-13T01:02:49.223548Z",
+     "shell.execute_reply": "2024-02-13T01:02:49.222908Z"
     },
     "id": "wL3ngCnuLEWd"
    },
diff --git a/master/tutorials/multiannotator.ipynb b/master/tutorials/multiannotator.ipynb
index fcc15b91e..2c00a3472 100644
--- a/master/tutorials/multiannotator.ipynb
+++ b/master/tutorials/multiannotator.ipynb
@@ -89,10 +89,10 @@
    "id": "a3ddc95f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:44.932005Z",
-     "iopub.status.busy": "2024-02-13T00:37:44.931601Z",
-     "iopub.status.idle": "2024-02-13T00:37:45.972699Z",
-     "shell.execute_reply": "2024-02-13T00:37:45.972092Z"
+     "iopub.execute_input": "2024-02-13T01:02:52.661602Z",
+     "iopub.status.busy": "2024-02-13T01:02:52.661190Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.734707Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.734066Z"
     },
     "nbsphinx": "hidden"
    },
@@ -102,7 +102,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -136,10 +136,10 @@
    "id": "c4efd119",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:45.975225Z",
-     "iopub.status.busy": "2024-02-13T00:37:45.974955Z",
-     "iopub.status.idle": "2024-02-13T00:37:45.978111Z",
-     "shell.execute_reply": "2024-02-13T00:37:45.977577Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.737582Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.737271Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.740704Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.740129Z"
     }
    },
    "outputs": [],
@@ -264,10 +264,10 @@
    "id": "c37c0a69",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:45.980351Z",
-     "iopub.status.busy": "2024-02-13T00:37:45.979885Z",
-     "iopub.status.idle": "2024-02-13T00:37:45.987655Z",
-     "shell.execute_reply": "2024-02-13T00:37:45.987087Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.742946Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.742601Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.750330Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.749869Z"
     },
     "nbsphinx": "hidden"
    },
@@ -351,10 +351,10 @@
    "id": "99f69523",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:45.989596Z",
-     "iopub.status.busy": "2024-02-13T00:37:45.989277Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.036506Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.036090Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.752459Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.752125Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.800557Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.800055Z"
     }
    },
    "outputs": [],
@@ -380,10 +380,10 @@
    "id": "8f241c16",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.038619Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.038244Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.055804Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.055338Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.802985Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.802640Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.820098Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.819649Z"
     }
    },
    "outputs": [
@@ -598,10 +598,10 @@
    "id": "4f0819ba",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.057855Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.057526Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.061414Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.060976Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.822293Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.821960Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.825813Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.825373Z"
     }
    },
    "outputs": [
@@ -672,10 +672,10 @@
    "id": "d009f347",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.063516Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.063128Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.092469Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.091907Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.827796Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.827641Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.854664Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.854145Z"
     }
    },
    "outputs": [],
@@ -699,10 +699,10 @@
    "id": "cbd1e415",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.094643Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.094316Z",
-     "iopub.status.idle": "2024-02-13T00:37:46.120466Z",
-     "shell.execute_reply": "2024-02-13T00:37:46.120024Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.857515Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.857114Z",
+     "iopub.status.idle": "2024-02-13T01:02:53.884830Z",
+     "shell.execute_reply": "2024-02-13T01:02:53.884388Z"
     }
    },
    "outputs": [],
@@ -739,10 +739,10 @@
    "id": "6ca92617",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:46.122412Z",
-     "iopub.status.busy": "2024-02-13T00:37:46.122096Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.897477Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.896981Z"
+     "iopub.execute_input": "2024-02-13T01:02:53.886959Z",
+     "iopub.status.busy": "2024-02-13T01:02:53.886631Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.700403Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.699824Z"
     }
    },
    "outputs": [],
@@ -772,10 +772,10 @@
    "id": "bf945113",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.900018Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.899596Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.906288Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.905738Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.703078Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.702551Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.709491Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.708927Z"
     },
     "scrolled": true
    },
@@ -886,10 +886,10 @@
    "id": "14251ee0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.908268Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.907956Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.920189Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.919649Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.711588Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.711258Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.723565Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.723092Z"
     }
    },
    "outputs": [
@@ -1139,10 +1139,10 @@
    "id": "efe16638",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.922098Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.921787Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.928124Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.927682Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.725578Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.725251Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.731542Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.731090Z"
     },
     "scrolled": true
    },
@@ -1316,10 +1316,10 @@
    "id": "abd0fb0b",
    "metadata": {
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-     "iopub.execute_input": "2024-02-13T00:37:47.930079Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.929760Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.932903Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.932479Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.733517Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.733188Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.735876Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.735414Z"
     }
    },
    "outputs": [],
@@ -1341,10 +1341,10 @@
    "id": "cdf061df",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.934798Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.934474Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.937711Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.937181Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.737822Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.737505Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.741036Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.740591Z"
     },
     "scrolled": true
    },
@@ -1396,10 +1396,10 @@
    "id": "08949890",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.939701Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.939386Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.941815Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.941384Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.743034Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.742705Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.745337Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.744893Z"
     }
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    "outputs": [],
@@ -1423,10 +1423,10 @@
    "id": "6948b073",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.943801Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.943429Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.947682Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.947148Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.747247Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.746933Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.751016Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.750516Z"
     }
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    "outputs": [
@@ -1481,10 +1481,10 @@
    "id": "6f8e6914",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.949625Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.949310Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.978169Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.977598Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.753149Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.752751Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.781554Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.780971Z"
     }
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    "outputs": [],
@@ -1527,10 +1527,10 @@
    "id": "b806d2ea",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:47.980456Z",
-     "iopub.status.busy": "2024-02-13T00:37:47.980036Z",
-     "iopub.status.idle": "2024-02-13T00:37:47.984796Z",
-     "shell.execute_reply": "2024-02-13T00:37:47.984246Z"
+     "iopub.execute_input": "2024-02-13T01:02:55.783903Z",
+     "iopub.status.busy": "2024-02-13T01:02:55.783584Z",
+     "iopub.status.idle": "2024-02-13T01:02:55.788275Z",
+     "shell.execute_reply": "2024-02-13T01:02:55.787745Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/tutorials/multilabel_classification.ipynb b/master/tutorials/multilabel_classification.ipynb
index 0e1a55f3f..f029d0169 100644
--- a/master/tutorials/multilabel_classification.ipynb
+++ b/master/tutorials/multilabel_classification.ipynb
@@ -64,10 +64,10 @@
    "id": "7383d024-8273-4039-bccd-aab3020d331f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:50.650771Z",
-     "iopub.status.busy": "2024-02-13T00:37:50.650550Z",
-     "iopub.status.idle": "2024-02-13T00:37:51.774800Z",
-     "shell.execute_reply": "2024-02-13T00:37:51.774125Z"
+     "iopub.execute_input": "2024-02-13T01:02:58.768811Z",
+     "iopub.status.busy": "2024-02-13T01:02:58.768396Z",
+     "iopub.status.idle": "2024-02-13T01:02:59.880006Z",
+     "shell.execute_reply": "2024-02-13T01:02:59.879407Z"
     },
     "nbsphinx": "hidden"
    },
@@ -79,7 +79,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -105,10 +105,10 @@
    "id": "bf9101d8-b1a9-4305-b853-45aaf3d67a69",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:51.777390Z",
-     "iopub.status.busy": "2024-02-13T00:37:51.777090Z",
-     "iopub.status.idle": "2024-02-13T00:37:51.979058Z",
-     "shell.execute_reply": "2024-02-13T00:37:51.978498Z"
+     "iopub.execute_input": "2024-02-13T01:02:59.882450Z",
+     "iopub.status.busy": "2024-02-13T01:02:59.882189Z",
+     "iopub.status.idle": "2024-02-13T01:03:00.080766Z",
+     "shell.execute_reply": "2024-02-13T01:03:00.080087Z"
     }
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    "outputs": [],
@@ -268,10 +268,10 @@
    "id": "e8ff5c2f-bd52-44aa-b307-b2b634147c68",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:51.981825Z",
-     "iopub.status.busy": "2024-02-13T00:37:51.981245Z",
-     "iopub.status.idle": "2024-02-13T00:37:51.994150Z",
-     "shell.execute_reply": "2024-02-13T00:37:51.993656Z"
+     "iopub.execute_input": "2024-02-13T01:03:00.083792Z",
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+     "iopub.status.idle": "2024-02-13T01:03:00.096677Z",
+     "shell.execute_reply": "2024-02-13T01:03:00.096078Z"
     },
     "nbsphinx": "hidden"
    },
@@ -407,10 +407,10 @@
    "id": "dac65d3b-51e8-4682-b829-beab610b56d6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:51.996322Z",
-     "iopub.status.busy": "2024-02-13T00:37:51.995977Z",
-     "iopub.status.idle": "2024-02-13T00:37:54.679288Z",
-     "shell.execute_reply": "2024-02-13T00:37:54.678681Z"
+     "iopub.execute_input": "2024-02-13T01:03:00.099005Z",
+     "iopub.status.busy": "2024-02-13T01:03:00.098612Z",
+     "iopub.status.idle": "2024-02-13T01:03:02.722167Z",
+     "shell.execute_reply": "2024-02-13T01:03:02.721597Z"
     }
    },
    "outputs": [
@@ -454,10 +454,10 @@
    "id": "b5fa99a9-2583-4cd0-9d40-015f698cdb23",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:54.681640Z",
-     "iopub.status.busy": "2024-02-13T00:37:54.681268Z",
-     "iopub.status.idle": "2024-02-13T00:37:56.039215Z",
-     "shell.execute_reply": "2024-02-13T00:37:56.038664Z"
+     "iopub.execute_input": "2024-02-13T01:03:02.724722Z",
+     "iopub.status.busy": "2024-02-13T01:03:02.724201Z",
+     "iopub.status.idle": "2024-02-13T01:03:04.069993Z",
+     "shell.execute_reply": "2024-02-13T01:03:04.069438Z"
     }
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    "outputs": [],
@@ -499,10 +499,10 @@
    "id": "ac1a60df",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:56.041719Z",
-     "iopub.status.busy": "2024-02-13T00:37:56.041286Z",
-     "iopub.status.idle": "2024-02-13T00:37:56.045310Z",
-     "shell.execute_reply": "2024-02-13T00:37:56.044765Z"
+     "iopub.execute_input": "2024-02-13T01:03:04.072445Z",
+     "iopub.status.busy": "2024-02-13T01:03:04.072108Z",
+     "iopub.status.idle": "2024-02-13T01:03:04.075799Z",
+     "shell.execute_reply": "2024-02-13T01:03:04.075259Z"
     }
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    "outputs": [
@@ -544,10 +544,10 @@
    "id": "d09115b6-ad44-474f-9c8a-85a459586439",
    "metadata": {
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-     "iopub.execute_input": "2024-02-13T00:37:56.047526Z",
-     "iopub.status.busy": "2024-02-13T00:37:56.047149Z",
-     "iopub.status.idle": "2024-02-13T00:37:57.846739Z",
-     "shell.execute_reply": "2024-02-13T00:37:57.846141Z"
+     "iopub.execute_input": "2024-02-13T01:03:04.077763Z",
+     "iopub.status.busy": "2024-02-13T01:03:04.077443Z",
+     "iopub.status.idle": "2024-02-13T01:03:05.915145Z",
+     "shell.execute_reply": "2024-02-13T01:03:05.914526Z"
     }
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    "outputs": [
@@ -594,10 +594,10 @@
    "id": "c18dd83b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:57.849517Z",
-     "iopub.status.busy": "2024-02-13T00:37:57.848710Z",
-     "iopub.status.idle": "2024-02-13T00:37:57.856343Z",
-     "shell.execute_reply": "2024-02-13T00:37:57.855894Z"
+     "iopub.execute_input": "2024-02-13T01:03:05.917885Z",
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+     "iopub.status.idle": "2024-02-13T01:03:05.924933Z",
+     "shell.execute_reply": "2024-02-13T01:03:05.924469Z"
     }
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    "outputs": [
@@ -633,10 +633,10 @@
    "id": "fffa88f6-84d7-45fe-8214-0e22079a06d1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:37:57.858417Z",
-     "iopub.status.busy": "2024-02-13T00:37:57.858103Z",
-     "iopub.status.idle": "2024-02-13T00:38:00.434248Z",
-     "shell.execute_reply": "2024-02-13T00:38:00.433629Z"
+     "iopub.execute_input": "2024-02-13T01:03:05.926896Z",
+     "iopub.status.busy": "2024-02-13T01:03:05.926639Z",
+     "iopub.status.idle": "2024-02-13T01:03:08.486417Z",
+     "shell.execute_reply": "2024-02-13T01:03:08.485824Z"
     }
    },
    "outputs": [
@@ -671,10 +671,10 @@
    "id": "c1198575",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:00.436547Z",
-     "iopub.status.busy": "2024-02-13T00:38:00.436204Z",
-     "iopub.status.idle": "2024-02-13T00:38:00.439580Z",
-     "shell.execute_reply": "2024-02-13T00:38:00.439055Z"
+     "iopub.execute_input": "2024-02-13T01:03:08.488686Z",
+     "iopub.status.busy": "2024-02-13T01:03:08.488363Z",
+     "iopub.status.idle": "2024-02-13T01:03:08.492007Z",
+     "shell.execute_reply": "2024-02-13T01:03:08.491449Z"
     }
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    "outputs": [
@@ -721,10 +721,10 @@
    "id": "49161b19-7625-4fb7-add9-607d91a7eca1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:00.441604Z",
-     "iopub.status.busy": "2024-02-13T00:38:00.441278Z",
-     "iopub.status.idle": "2024-02-13T00:38:00.445327Z",
-     "shell.execute_reply": "2024-02-13T00:38:00.444780Z"
+     "iopub.execute_input": "2024-02-13T01:03:08.494000Z",
+     "iopub.status.busy": "2024-02-13T01:03:08.493695Z",
+     "iopub.status.idle": "2024-02-13T01:03:08.498016Z",
+     "shell.execute_reply": "2024-02-13T01:03:08.497458Z"
     }
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    "outputs": [],
@@ -752,10 +752,10 @@
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-     "iopub.execute_input": "2024-02-13T00:38:00.447305Z",
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-     "iopub.status.idle": "2024-02-13T00:38:00.450668Z",
-     "shell.execute_reply": "2024-02-13T00:38:00.450247Z"
+     "iopub.execute_input": "2024-02-13T01:03:08.500025Z",
+     "iopub.status.busy": "2024-02-13T01:03:08.499720Z",
+     "iopub.status.idle": "2024-02-13T01:03:08.502936Z",
+     "shell.execute_reply": "2024-02-13T01:03:08.502394Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/tutorials/object_detection.ipynb b/master/tutorials/object_detection.ipynb
index 15426f4ed..108bde32a 100644
--- a/master/tutorials/object_detection.ipynb
+++ b/master/tutorials/object_detection.ipynb
@@ -70,10 +70,10 @@
    "id": "0ba0dc70",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:02.954217Z",
-     "iopub.status.busy": "2024-02-13T00:38:02.954031Z",
-     "iopub.status.idle": "2024-02-13T00:38:04.091043Z",
-     "shell.execute_reply": "2024-02-13T00:38:04.090401Z"
+     "iopub.execute_input": "2024-02-13T01:03:11.142056Z",
+     "iopub.status.busy": "2024-02-13T01:03:11.141857Z",
+     "iopub.status.idle": "2024-02-13T01:03:12.303193Z",
+     "shell.execute_reply": "2024-02-13T01:03:12.302666Z"
     },
     "nbsphinx": "hidden"
    },
@@ -83,7 +83,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -109,10 +109,10 @@
    "id": "c90449c8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:04.093582Z",
-     "iopub.status.busy": "2024-02-13T00:38:04.093297Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.237712Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.237027Z"
+     "iopub.execute_input": "2024-02-13T01:03:12.305972Z",
+     "iopub.status.busy": "2024-02-13T01:03:12.305454Z",
+     "iopub.status.idle": "2024-02-13T01:03:13.728705Z",
+     "shell.execute_reply": "2024-02-13T01:03:13.728015Z"
     }
    },
    "outputs": [],
@@ -130,10 +130,10 @@
    "id": "df8be4c6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:05.240179Z",
-     "iopub.status.busy": "2024-02-13T00:38:05.239978Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.243407Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.242873Z"
+     "iopub.execute_input": "2024-02-13T01:03:13.731213Z",
+     "iopub.status.busy": "2024-02-13T01:03:13.731013Z",
+     "iopub.status.idle": "2024-02-13T01:03:13.734130Z",
+     "shell.execute_reply": "2024-02-13T01:03:13.733674Z"
     }
    },
    "outputs": [],
@@ -169,10 +169,10 @@
    "id": "2e9ffd6f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:05.245459Z",
-     "iopub.status.busy": "2024-02-13T00:38:05.245057Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.252238Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.251811Z"
+     "iopub.execute_input": "2024-02-13T01:03:13.736193Z",
+     "iopub.status.busy": "2024-02-13T01:03:13.735849Z",
+     "iopub.status.idle": "2024-02-13T01:03:13.742674Z",
+     "shell.execute_reply": "2024-02-13T01:03:13.742242Z"
     }
    },
    "outputs": [],
@@ -198,10 +198,10 @@
    "id": "56705562",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:05.254315Z",
-     "iopub.status.busy": "2024-02-13T00:38:05.254000Z",
-     "iopub.status.idle": "2024-02-13T00:38:05.742554Z",
-     "shell.execute_reply": "2024-02-13T00:38:05.741944Z"
+     "iopub.execute_input": "2024-02-13T01:03:13.744769Z",
+     "iopub.status.busy": "2024-02-13T01:03:13.744583Z",
+     "iopub.status.idle": "2024-02-13T01:03:14.236517Z",
+     "shell.execute_reply": "2024-02-13T01:03:14.235931Z"
     },
     "scrolled": true
    },
@@ -242,10 +242,10 @@
    "id": "b08144d7",
    "metadata": {
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-     "iopub.execute_input": "2024-02-13T00:38:05.744999Z",
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-     "shell.execute_reply": "2024-02-13T00:38:05.749469Z"
+     "iopub.execute_input": "2024-02-13T01:03:14.239143Z",
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@@ -497,10 +497,10 @@
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@@ -557,10 +557,10 @@
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@@ -660,10 +660,10 @@
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@@ -700,10 +700,10 @@
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@@ -762,10 +762,10 @@
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@@ -812,10 +812,10 @@
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@@ -862,10 +862,10 @@
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@@ -925,10 +925,10 @@
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@@ -971,10 +971,10 @@
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@@ -1017,10 +1017,10 @@
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@@ -1067,10 +1067,10 @@
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@@ -1090,10 +1090,10 @@
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@@ -1172,10 +1172,10 @@
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@@ -1214,10 +1214,10 @@
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    "id": "47b6a8ff-7a58-4a1f-baee-e6cfe7a85a6d",
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    2. Pre-process the Cifar10 dataset
    
 
 
    
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    3. Use cleanlab and feature embeddings to find outliers in the data
 
    
 
    
-
    
+
 
 
    
 
    
@@ -1936,7 +1520,7 @@ 
    4. Use cleanlab and here.
    
 
 
  
diff --git a/master/tutorials/outliers.ipynb b/master/tutorials/outliers.ipynb
index 85bfdbf77..2fd4d0b8b 100644
--- a/master/tutorials/outliers.ipynb
+++ b/master/tutorials/outliers.ipynb
@@ -109,10 +109,10 @@
    "id": "2bbebfc8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:13.538819Z",
-     "iopub.status.busy": "2024-02-13T00:38:13.538332Z",
-     "iopub.status.idle": "2024-02-13T00:38:16.310196Z",
-     "shell.execute_reply": "2024-02-13T00:38:16.309618Z"
+     "iopub.execute_input": "2024-02-13T01:03:21.946350Z",
+     "iopub.status.busy": "2024-02-13T01:03:21.946175Z",
+     "iopub.status.idle": "2024-02-13T01:03:24.693428Z",
+     "shell.execute_reply": "2024-02-13T01:03:24.692797Z"
     },
     "nbsphinx": "hidden"
    },
@@ -125,7 +125,7 @@
     "dependencies = [\"matplotlib\", \"torch\", \"torchvision\", \"timm\", \"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -159,10 +159,10 @@
    "id": "4396f544",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:16.312856Z",
-     "iopub.status.busy": "2024-02-13T00:38:16.312401Z",
-     "iopub.status.idle": "2024-02-13T00:38:16.652112Z",
-     "shell.execute_reply": "2024-02-13T00:38:16.651552Z"
+     "iopub.execute_input": "2024-02-13T01:03:24.696184Z",
+     "iopub.status.busy": "2024-02-13T01:03:24.695863Z",
+     "iopub.status.idle": "2024-02-13T01:03:25.047975Z",
+     "shell.execute_reply": "2024-02-13T01:03:25.047451Z"
     }
    },
    "outputs": [],
@@ -188,10 +188,10 @@
    "id": "3792f82e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:16.654843Z",
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-     "iopub.status.idle": "2024-02-13T00:38:16.658614Z",
-     "shell.execute_reply": "2024-02-13T00:38:16.658201Z"
+     "iopub.execute_input": "2024-02-13T01:03:25.050426Z",
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+     "shell.execute_reply": "2024-02-13T01:03:25.053845Z"
     },
     "nbsphinx": "hidden"
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@@ -225,10 +225,10 @@
    "id": "fd853a54",
    "metadata": {
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-     "shell.execute_reply": "2024-02-13T00:38:22.676909Z"
+     "iopub.execute_input": "2024-02-13T01:03:25.056210Z",
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+     "iopub.status.idle": "2024-02-13T01:03:29.390845Z",
+     "shell.execute_reply": "2024-02-13T01:03:29.390321Z"
     }
    },
    "outputs": [
@@ -252,7 +252,7 @@
      "output_type": "stream",
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       "\r",
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+      " 21%|██        | 34963456/170498071 [00:00<00:01, 96191879.75it/s]"
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      "output_type": "stream",
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+      " 39%|███▉      | 67141632/170498071 [00:00<00:00, 104252034.08it/s]"
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+      " 46%|████▌     | 77856768/170498071 [00:00<00:00, 105125468.20it/s]"
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+      " 52%|█████▏    | 88899584/170498071 [00:00<00:00, 106705587.58it/s]"
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+      " 58%|█████▊    | 99581952/170498071 [00:01<00:00, 105304746.58it/s]"
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+      " 65%|██████▍   | 110395392/170498071 [00:01<00:00, 106104853.34it/s]"
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       "\r",
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+      " 78%|███████▊  | 132677632/170498071 [00:01<00:00, 108681810.16it/s]"
      ]
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      "text": [
       "\r",
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+      " 84%|████████▍ | 143818752/170498071 [00:01<00:00, 109445329.99it/s]"
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+      " 91%|█████████ | 154927104/170498071 [00:01<00:00, 109907364.09it/s]"
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-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "100%|██████████| 170498071/170498071 [00:03<00:00, 50407814.33it/s]"
+      "100%|██████████| 170498071/170498071 [00:01<00:00, 103483721.82it/s]"
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@@ -626,10 +498,10 @@
    "id": "9b64e0aa",
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-     "shell.execute_reply": "2024-02-13T00:38:22.683763Z"
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@@ -680,10 +552,10 @@
    "id": "a00aa3ed",
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@@ -716,10 +588,10 @@
    "id": "41e5cb6b",
    "metadata": {
     "execution": {
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@@ -757,10 +629,10 @@
    "id": "1cf25354",
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@@ -783,17 +655,17 @@
    "id": "85a58d41",
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-     "shell.execute_reply": "2024-02-13T00:38:36.440695Z"
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+     "shell.execute_reply": "2024-02-13T01:03:43.147490Z"
     }
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    "outputs": [
     {
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-       "model_id": "ff543fd6f30d4622be8edea1bc3715b0",
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@@ -852,10 +724,10 @@
    "id": "feb0f519",
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-     "shell.execute_reply": "2024-02-13T00:38:38.033012Z"
+     "iopub.execute_input": "2024-02-13T01:03:43.150246Z",
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+     "shell.execute_reply": "2024-02-13T01:03:44.712038Z"
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@@ -899,10 +771,10 @@
    "id": "089d5860",
    "metadata": {
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-     "shell.execute_reply": "2024-02-13T00:38:38.466065Z"
+     "iopub.execute_input": "2024-02-13T01:03:44.715052Z",
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@@ -938,10 +810,10 @@
    "id": "78b1951c",
    "metadata": {
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-     "shell.execute_reply": "2024-02-13T00:38:39.119993Z"
+     "iopub.execute_input": "2024-02-13T01:03:45.142428Z",
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@@ -991,10 +863,10 @@
    "id": "e9dff81b",
    "metadata": {
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-     "shell.execute_reply": "2024-02-13T00:38:39.461013Z"
+     "iopub.execute_input": "2024-02-13T01:03:45.804974Z",
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@@ -1042,10 +914,10 @@
    "id": "616769f8",
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2024-02-13T00:38:39.705868Z"
+     "iopub.execute_input": "2024-02-13T01:03:46.152129Z",
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@@ -1101,10 +973,10 @@
    "id": "40fed4ef",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:38:39.709202Z",
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-     "shell.execute_reply": "2024-02-13T00:38:39.795019Z"
+     "iopub.execute_input": "2024-02-13T01:03:46.387276Z",
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     }
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@@ -1125,10 +997,10 @@
    "id": "89f9db72",
    "metadata": {
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+     "iopub.execute_input": "2024-02-13T01:03:46.475190Z",
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@@ -1165,10 +1037,10 @@
    "id": "874c885a",
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-     "shell.execute_reply": "2024-02-13T00:38:51.748688Z"
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@@ -1199,10 +1071,10 @@
    "id": "e110fc4b",
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-     "iopub.execute_input": "2024-02-13T00:38:51.752032Z",
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-     "iopub.status.idle": "2024-02-13T00:38:51.953634Z",
-     "shell.execute_reply": "2024-02-13T00:38:51.953124Z"
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@@ -1216,10 +1088,10 @@
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-     "iopub.execute_input": "2024-02-13T00:38:51.956085Z",
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-     "shell.execute_reply": "2024-02-13T00:38:51.959036Z"
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@@ -1241,10 +1113,10 @@
    "id": "17f96fa6",
    "metadata": {
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-     "shell.execute_reply": "2024-02-13T00:38:51.968771Z"
+     "iopub.execute_input": "2024-02-13T01:03:58.955699Z",
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+     "shell.execute_reply": "2024-02-13T01:03:58.963008Z"
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@@ -1289,7 +1161,7 @@
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@@ -1304,15 +1176,15 @@
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        "description": "",
        "description_allow_html": false,
-       "layout": "IPY_MODEL_8ceb374fbc2f4adc96b72f019eac0d7b",
+       "layout": "IPY_MODEL_c067481e2c854162a43a69832dafac1d",
        "placeholder": "​",
-       "style": "IPY_MODEL_a4b4f176039345ef88ce5d31b744e86f",
+       "style": "IPY_MODEL_e255456cdbd940b1a0871b4201ff7f13",
        "tabbable": null,
        "tooltip": null,
-       "value": "model.safetensors: 100%"
+       "value": " 102M/102M [00:00<00:00, 187MB/s]"
       }
      },
-     "3a6eff6e7a34490286388705121c5109": {
+     "28c1892184834bbb9e428562668c27bf": {
       "model_module": "@jupyter-widgets/base",
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@@ -1365,25 +1237,7 @@
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-     "68d6368b9f4e4091939374ceb23813bc": {
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-     "8ceb374fbc2f4adc96b72f019eac0d7b": {
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@@ -1436,7 +1290,80 @@
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-     "8f9e6f5d41ec42ad847534bfdb6bd26f": {
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+       "layout": "IPY_MODEL_af967ea5935e411f8a1ce18e0fb360f0",
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+     "a16c2d0853d4451887b15287af0107a9": {
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+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "ProgressView",
+       "bar_style": "success",
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+       "description_allow_html": false,
+       "layout": "IPY_MODEL_7ae945316e554eb5abaaca7e1881a842",
+       "max": 102469840.0,
+       "min": 0.0,
+       "orientation": "horizontal",
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+       "_model_module_version": "2.0.0",
+       "_model_name": "HTMLModel",
+       "_view_count": null,
+       "_view_module": "@jupyter-widgets/controls",
+       "_view_module_version": "2.0.0",
+       "_view_name": "HTMLView",
+       "description": "",
+       "description_allow_html": false,
+       "layout": "IPY_MODEL_28c1892184834bbb9e428562668c27bf",
+       "placeholder": "​",
+       "style": "IPY_MODEL_f8c09f90aad44bef847738e3e859f017",
+       "tabbable": null,
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@@ -1489,51 +1416,7 @@
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-       "bar_style": "success",
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-       "layout": "IPY_MODEL_3a6eff6e7a34490286388705121c5109",
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-     "de53c221b897471d9ee2bad1f34bd6ad": {
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@@ -1586,30 +1469,25 @@
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        "_model_module_version": "2.0.0",
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-       "_view_module": "@jupyter-widgets/controls",
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-       "description": "",
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-       "placeholder": "​",
-       "style": "IPY_MODEL_68d6368b9f4e4091939374ceb23813bc",
-       "tabbable": null,
-       "tooltip": null,
-       "value": " 102M/102M [00:00<00:00, 164MB/s]"
+       "_view_name": "StyleView",
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@@ -1625,28 +1503,22 @@
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        "_model_module_version": "2.0.0",
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diff --git a/master/tutorials/regression.ipynb b/master/tutorials/regression.ipynb
index c43233657..f45de88ba 100644
--- a/master/tutorials/regression.ipynb
+++ b/master/tutorials/regression.ipynb
@@ -102,10 +102,10 @@
    "id": "2e1af7d8",
    "metadata": {
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-     "iopub.status.busy": "2024-02-13T00:38:56.418538Z",
-     "iopub.status.idle": "2024-02-13T00:38:57.502296Z",
-     "shell.execute_reply": "2024-02-13T00:38:57.501688Z"
+     "iopub.execute_input": "2024-02-13T01:04:03.295564Z",
+     "iopub.status.busy": "2024-02-13T01:04:03.295384Z",
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@@ -117,7 +117,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib>=3.6.0\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = \" \".join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -143,10 +143,10 @@
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-     "shell.execute_reply": "2024-02-13T00:38:57.522014Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.473255Z",
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@@ -165,10 +165,10 @@
    "id": "284dc264",
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-     "shell.execute_reply": "2024-02-13T00:38:57.527014Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.495177Z",
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@@ -199,10 +199,10 @@
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-     "iopub.status.idle": "2024-02-13T00:38:57.604240Z",
-     "shell.execute_reply": "2024-02-13T00:38:57.603695Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.500196Z",
+     "iopub.status.busy": "2024-02-13T01:04:04.499813Z",
+     "iopub.status.idle": "2024-02-13T01:04:04.611611Z",
+     "shell.execute_reply": "2024-02-13T01:04:04.610989Z"
     }
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    "outputs": [
@@ -375,10 +375,10 @@
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-     "shell.execute_reply": "2024-02-13T00:38:57.783443Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.613792Z",
+     "iopub.status.busy": "2024-02-13T01:04:04.613601Z",
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+     "shell.execute_reply": "2024-02-13T01:04:04.805077Z"
     },
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@@ -418,10 +418,10 @@
    "id": "df5a0f59",
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-     "shell.execute_reply": "2024-02-13T00:38:58.025843Z"
+     "iopub.execute_input": "2024-02-13T01:04:04.808407Z",
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+     "iopub.status.idle": "2024-02-13T01:04:05.060992Z",
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@@ -457,10 +457,10 @@
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+     "iopub.execute_input": "2024-02-13T01:04:05.063164Z",
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@@ -478,10 +478,10 @@
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-     "shell.execute_reply": "2024-02-13T00:38:58.039514Z"
+     "iopub.execute_input": "2024-02-13T01:04:05.069776Z",
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@@ -884,10 +884,10 @@
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@@ -922,10 +922,10 @@
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@@ -964,10 +964,10 @@
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@@ -1023,10 +1023,10 @@
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diff --git a/master/tutorials/segmentation.html b/master/tutorials/segmentation.html
index 1c0d0f267..58200e580 100644
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    3. Use cleanlab to find label issues
 
    
 
    
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    Classes which are commonly mislabeled overall
    
 
 
    
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    Get label quality scores
 
    
 
    
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    Beyond scoring the overall label quality of each image, the above method produces a (0 to 1) quality score for each pixel. We can apply a thresholding function to these scores in order to extract the same style True or False mask as find_label_issues().
    
 
    
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    Get label quality scores
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diff --git a/master/tutorials/segmentation.ipynb b/master/tutorials/segmentation.ipynb
index 2c84a07e4..5a19416ec 100644
--- a/master/tutorials/segmentation.ipynb
+++ b/master/tutorials/segmentation.ipynb
@@ -61,10 +61,10 @@
    "id": "ae8a08e0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:39:16.016581Z",
-     "iopub.status.busy": "2024-02-13T00:39:16.016411Z",
-     "iopub.status.idle": "2024-02-13T00:39:17.846185Z",
-     "shell.execute_reply": "2024-02-13T00:39:17.845532Z"
+     "iopub.execute_input": "2024-02-13T01:04:24.456211Z",
+     "iopub.status.busy": "2024-02-13T01:04:24.456033Z",
+     "iopub.status.idle": "2024-02-13T01:04:26.961154Z",
+     "shell.execute_reply": "2024-02-13T01:04:26.960465Z"
     }
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    "outputs": [],
@@ -79,10 +79,10 @@
    "id": "58fd4c55",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:39:17.848857Z",
-     "iopub.status.busy": "2024-02-13T00:39:17.848507Z",
-     "iopub.status.idle": "2024-02-13T00:40:20.168637Z",
-     "shell.execute_reply": "2024-02-13T00:40:20.167980Z"
+     "iopub.execute_input": "2024-02-13T01:04:26.963827Z",
+     "iopub.status.busy": "2024-02-13T01:04:26.963606Z",
+     "iopub.status.idle": "2024-02-13T01:06:05.695134Z",
+     "shell.execute_reply": "2024-02-13T01:06:05.694398Z"
     }
    },
    "outputs": [],
@@ -97,10 +97,10 @@
    "id": "439b0305",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:20.170997Z",
-     "iopub.status.busy": "2024-02-13T00:40:20.170812Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.217733Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.217103Z"
+     "iopub.execute_input": "2024-02-13T01:06:05.697918Z",
+     "iopub.status.busy": "2024-02-13T01:06:05.697527Z",
+     "iopub.status.idle": "2024-02-13T01:06:06.776866Z",
+     "shell.execute_reply": "2024-02-13T01:06:06.776248Z"
     },
     "nbsphinx": "hidden"
    },
@@ -111,7 +111,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -137,10 +137,10 @@
    "id": "a1349304",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:21.220218Z",
-     "iopub.status.busy": "2024-02-13T00:40:21.219949Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.223254Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.222838Z"
+     "iopub.execute_input": "2024-02-13T01:06:06.779676Z",
+     "iopub.status.busy": "2024-02-13T01:06:06.779211Z",
+     "iopub.status.idle": "2024-02-13T01:06:06.782966Z",
+     "shell.execute_reply": "2024-02-13T01:06:06.782526Z"
     }
    },
    "outputs": [],
@@ -203,10 +203,10 @@
    "id": "07dc5678",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:21.225373Z",
-     "iopub.status.busy": "2024-02-13T00:40:21.225050Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.228867Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.228454Z"
+     "iopub.execute_input": "2024-02-13T01:06:06.784992Z",
+     "iopub.status.busy": "2024-02-13T01:06:06.784723Z",
+     "iopub.status.idle": "2024-02-13T01:06:06.788767Z",
+     "shell.execute_reply": "2024-02-13T01:06:06.788300Z"
     }
    },
    "outputs": [
@@ -247,10 +247,10 @@
    "id": "25ebe22a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:21.230771Z",
-     "iopub.status.busy": "2024-02-13T00:40:21.230493Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.234013Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.233591Z"
+     "iopub.execute_input": "2024-02-13T01:06:06.790688Z",
+     "iopub.status.busy": "2024-02-13T01:06:06.790377Z",
+     "iopub.status.idle": "2024-02-13T01:06:06.793892Z",
+     "shell.execute_reply": "2024-02-13T01:06:06.793425Z"
     }
    },
    "outputs": [
@@ -290,10 +290,10 @@
    "id": "3faedea9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:40:21.235957Z",
-     "iopub.status.busy": "2024-02-13T00:40:21.235652Z",
-     "iopub.status.idle": "2024-02-13T00:40:21.238285Z",
-     "shell.execute_reply": "2024-02-13T00:40:21.237864Z"
+     "iopub.execute_input": "2024-02-13T01:06:06.795857Z",
+     "iopub.status.busy": "2024-02-13T01:06:06.795538Z",
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@@ -333,17 +333,17 @@
    "id": "2c2ad9ad",
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+     "shell.execute_reply": "2024-02-13T01:07:22.998356Z"
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@@ -357,7 +357,7 @@
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@@ -400,10 +400,10 @@
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@@ -446,10 +446,10 @@
    "id": "57fed473",
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@@ -519,10 +519,10 @@
    "id": "e4a006bd",
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diff --git a/master/tutorials/tabular.ipynb b/master/tutorials/tabular.ipynb
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+     "shell.execute_reply": "2024-02-13T01:08:30.489507Z"
     },
     "nbsphinx": "hidden"
    },
@@ -125,7 +125,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -150,10 +150,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:43.898334Z",
-     "iopub.status.busy": "2024-02-13T00:42:43.897815Z",
-     "iopub.status.idle": "2024-02-13T00:42:43.921287Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.920802Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.492829Z",
+     "iopub.status.busy": "2024-02-13T01:08:30.492369Z",
+     "iopub.status.idle": "2024-02-13T01:08:30.516248Z",
+     "shell.execute_reply": "2024-02-13T01:08:30.515663Z"
     }
    },
    "outputs": [],
@@ -194,10 +194,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:43.923449Z",
-     "iopub.status.busy": "2024-02-13T00:42:43.923199Z",
-     "iopub.status.idle": "2024-02-13T00:42:43.970211Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.969737Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.518838Z",
+     "iopub.status.busy": "2024-02-13T01:08:30.518325Z",
+     "iopub.status.idle": "2024-02-13T01:08:30.650610Z",
+     "shell.execute_reply": "2024-02-13T01:08:30.650061Z"
     }
    },
    "outputs": [
@@ -304,10 +304,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:43.972223Z",
-     "iopub.status.busy": "2024-02-13T00:42:43.971895Z",
-     "iopub.status.idle": "2024-02-13T00:42:43.975341Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.974896Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.652633Z",
+     "iopub.status.busy": "2024-02-13T01:08:30.652455Z",
+     "iopub.status.idle": "2024-02-13T01:08:30.656208Z",
+     "shell.execute_reply": "2024-02-13T01:08:30.655751Z"
     }
    },
    "outputs": [],
@@ -328,10 +328,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:43.977060Z",
-     "iopub.status.busy": "2024-02-13T00:42:43.976888Z",
-     "iopub.status.idle": "2024-02-13T00:42:43.985075Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.984666Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.658256Z",
+     "iopub.status.busy": "2024-02-13T01:08:30.657954Z",
+     "iopub.status.idle": "2024-02-13T01:08:30.666462Z",
+     "shell.execute_reply": "2024-02-13T01:08:30.666011Z"
     }
    },
    "outputs": [],
@@ -383,10 +383,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:43.986964Z",
-     "iopub.status.busy": "2024-02-13T00:42:43.986788Z",
-     "iopub.status.idle": "2024-02-13T00:42:43.989432Z",
-     "shell.execute_reply": "2024-02-13T00:42:43.988974Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.668421Z",
+     "iopub.status.busy": "2024-02-13T01:08:30.668245Z",
+     "iopub.status.idle": "2024-02-13T01:08:30.670962Z",
+     "shell.execute_reply": "2024-02-13T01:08:30.670489Z"
     }
    },
    "outputs": [],
@@ -408,10 +408,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:43.991509Z",
-     "iopub.status.busy": "2024-02-13T00:42:43.991083Z",
-     "iopub.status.idle": "2024-02-13T00:42:44.509476Z",
-     "shell.execute_reply": "2024-02-13T00:42:44.508919Z"
+     "iopub.execute_input": "2024-02-13T01:08:30.672828Z",
+     "iopub.status.busy": "2024-02-13T01:08:30.672654Z",
+     "iopub.status.idle": "2024-02-13T01:08:31.202087Z",
+     "shell.execute_reply": "2024-02-13T01:08:31.201460Z"
     }
    },
    "outputs": [],
@@ -445,10 +445,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:44.511939Z",
-     "iopub.status.busy": "2024-02-13T00:42:44.511577Z",
-     "iopub.status.idle": "2024-02-13T00:42:46.185457Z",
-     "shell.execute_reply": "2024-02-13T00:42:46.184814Z"
+     "iopub.execute_input": "2024-02-13T01:08:31.204639Z",
+     "iopub.status.busy": "2024-02-13T01:08:31.204441Z",
+     "iopub.status.idle": "2024-02-13T01:08:32.925058Z",
+     "shell.execute_reply": "2024-02-13T01:08:32.924362Z"
     }
    },
    "outputs": [
@@ -480,10 +480,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:46.188122Z",
-     "iopub.status.busy": "2024-02-13T00:42:46.187581Z",
-     "iopub.status.idle": "2024-02-13T00:42:46.197623Z",
-     "shell.execute_reply": "2024-02-13T00:42:46.197181Z"
+     "iopub.execute_input": "2024-02-13T01:08:32.927748Z",
+     "iopub.status.busy": "2024-02-13T01:08:32.927142Z",
+     "iopub.status.idle": "2024-02-13T01:08:32.937409Z",
+     "shell.execute_reply": "2024-02-13T01:08:32.936870Z"
     }
    },
    "outputs": [
@@ -604,10 +604,10 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:46.199706Z",
-     "iopub.status.busy": "2024-02-13T00:42:46.199342Z",
-     "iopub.status.idle": "2024-02-13T00:42:46.203389Z",
-     "shell.execute_reply": "2024-02-13T00:42:46.202947Z"
+     "iopub.execute_input": "2024-02-13T01:08:32.939547Z",
+     "iopub.status.busy": "2024-02-13T01:08:32.939137Z",
+     "iopub.status.idle": "2024-02-13T01:08:32.943243Z",
+     "shell.execute_reply": "2024-02-13T01:08:32.942702Z"
     }
    },
    "outputs": [],
@@ -632,10 +632,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:46.205451Z",
-     "iopub.status.busy": "2024-02-13T00:42:46.205150Z",
-     "iopub.status.idle": "2024-02-13T00:42:46.212479Z",
-     "shell.execute_reply": "2024-02-13T00:42:46.212050Z"
+     "iopub.execute_input": "2024-02-13T01:08:32.945513Z",
+     "iopub.status.busy": "2024-02-13T01:08:32.945094Z",
+     "iopub.status.idle": "2024-02-13T01:08:32.952809Z",
+     "shell.execute_reply": "2024-02-13T01:08:32.952241Z"
     }
    },
    "outputs": [],
@@ -657,10 +657,10 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:46.214446Z",
-     "iopub.status.busy": "2024-02-13T00:42:46.214127Z",
-     "iopub.status.idle": "2024-02-13T00:42:46.324840Z",
-     "shell.execute_reply": "2024-02-13T00:42:46.324327Z"
+     "iopub.execute_input": "2024-02-13T01:08:32.955090Z",
+     "iopub.status.busy": "2024-02-13T01:08:32.954692Z",
+     "iopub.status.idle": "2024-02-13T01:08:33.067595Z",
+     "shell.execute_reply": "2024-02-13T01:08:33.066976Z"
     }
    },
    "outputs": [
@@ -690,10 +690,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:46.327188Z",
-     "iopub.status.busy": "2024-02-13T00:42:46.326779Z",
-     "iopub.status.idle": "2024-02-13T00:42:46.329720Z",
-     "shell.execute_reply": "2024-02-13T00:42:46.329164Z"
+     "iopub.execute_input": "2024-02-13T01:08:33.069839Z",
+     "iopub.status.busy": "2024-02-13T01:08:33.069415Z",
+     "iopub.status.idle": "2024-02-13T01:08:33.072322Z",
+     "shell.execute_reply": "2024-02-13T01:08:33.071796Z"
     }
    },
    "outputs": [],
@@ -714,10 +714,10 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:46.331798Z",
-     "iopub.status.busy": "2024-02-13T00:42:46.331427Z",
-     "iopub.status.idle": "2024-02-13T00:42:48.366698Z",
-     "shell.execute_reply": "2024-02-13T00:42:48.365922Z"
+     "iopub.execute_input": "2024-02-13T01:08:33.074205Z",
+     "iopub.status.busy": "2024-02-13T01:08:33.074028Z",
+     "iopub.status.idle": "2024-02-13T01:08:35.103168Z",
+     "shell.execute_reply": "2024-02-13T01:08:35.102538Z"
     }
    },
    "outputs": [],
@@ -737,10 +737,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:48.369882Z",
-     "iopub.status.busy": "2024-02-13T00:42:48.369266Z",
-     "iopub.status.idle": "2024-02-13T00:42:48.381941Z",
-     "shell.execute_reply": "2024-02-13T00:42:48.381371Z"
+     "iopub.execute_input": "2024-02-13T01:08:35.106336Z",
+     "iopub.status.busy": "2024-02-13T01:08:35.105516Z",
+     "iopub.status.idle": "2024-02-13T01:08:35.117507Z",
+     "shell.execute_reply": "2024-02-13T01:08:35.117029Z"
     }
    },
    "outputs": [
@@ -770,10 +770,10 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:48.384241Z",
-     "iopub.status.busy": "2024-02-13T00:42:48.383892Z",
-     "iopub.status.idle": "2024-02-13T00:42:48.415415Z",
-     "shell.execute_reply": "2024-02-13T00:42:48.414914Z"
+     "iopub.execute_input": "2024-02-13T01:08:35.119648Z",
+     "iopub.status.busy": "2024-02-13T01:08:35.119330Z",
+     "iopub.status.idle": "2024-02-13T01:08:35.175410Z",
+     "shell.execute_reply": "2024-02-13T01:08:35.174796Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/tutorials/text.html b/master/tutorials/text.html
index a117adbd0..86cab9796 100644
--- a/master/tutorials/text.html
+++ b/master/tutorials/text.html
@@ -733,7 +733,7 @@ 
    2. Load and format the text dataset
 
     This dataset has 10 classes.
-Classes: {'supported_cards_and_currencies', 'visa_or_mastercard', 'lost_or_stolen_phone', 'apple_pay_or_google_pay', 'getting_spare_card', 'cancel_transfer', 'card_payment_fee_charged', 'change_pin', 'beneficiary_not_allowed', 'card_about_to_expire'}
+Classes: {'cancel_transfer', 'apple_pay_or_google_pay', 'change_pin', 'beneficiary_not_allowed', 'lost_or_stolen_phone', 'visa_or_mastercard', 'getting_spare_card', 'supported_cards_and_currencies', 'card_about_to_expire', 'card_payment_fee_charged'}
 
    
 
 
    Let’s print the first example in the train set.
    
diff --git a/master/tutorials/text.ipynb b/master/tutorials/text.ipynb
index 18538d7df..3eb295acf 100644
--- a/master/tutorials/text.ipynb
+++ b/master/tutorials/text.ipynb
@@ -114,10 +114,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:51.470844Z",
-     "iopub.status.busy": "2024-02-13T00:42:51.470633Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.260427Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.259865Z"
+     "iopub.execute_input": "2024-02-13T01:08:38.092425Z",
+     "iopub.status.busy": "2024-02-13T01:08:38.092254Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.805897Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.805327Z"
     },
     "nbsphinx": "hidden"
    },
@@ -134,7 +134,7 @@
     "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\"  # disable parallelism to avoid deadlocks with huggingface\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -159,10 +159,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.263110Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.262566Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.265988Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.265540Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.808761Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.808186Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.811739Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.811146Z"
     }
    },
    "outputs": [],
@@ -184,10 +184,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.268097Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.267704Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.270840Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.270310Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.813751Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.813439Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.816553Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.816015Z"
     },
     "nbsphinx": "hidden"
    },
@@ -218,10 +218,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.272804Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.272618Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.315492Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.314934Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.818605Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.818269Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.868772Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.868239Z"
     }
    },
    "outputs": [
@@ -311,10 +311,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.317595Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.317320Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.320853Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.320398Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.871094Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.870690Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.874329Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.873872Z"
     }
    },
    "outputs": [],
@@ -329,10 +329,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.322935Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.322504Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.326062Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.325517Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.876570Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.876206Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.879535Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.878985Z"
     }
    },
    "outputs": [
@@ -341,7 +341,7 @@
      "output_type": "stream",
      "text": [
       "This dataset has 10 classes.\n",
-      "Classes: {'supported_cards_and_currencies', 'visa_or_mastercard', 'lost_or_stolen_phone', 'apple_pay_or_google_pay', 'getting_spare_card', 'cancel_transfer', 'card_payment_fee_charged', 'change_pin', 'beneficiary_not_allowed', 'card_about_to_expire'}\n"
+      "Classes: {'cancel_transfer', 'apple_pay_or_google_pay', 'change_pin', 'beneficiary_not_allowed', 'lost_or_stolen_phone', 'visa_or_mastercard', 'getting_spare_card', 'supported_cards_and_currencies', 'card_about_to_expire', 'card_payment_fee_charged'}\n"
      ]
     }
    ],
@@ -364,10 +364,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.328045Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.327855Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.331117Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.330553Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.881545Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.881247Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.884584Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.884114Z"
     }
    },
    "outputs": [
@@ -408,10 +408,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.333127Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.332818Z",
-     "iopub.status.idle": "2024-02-13T00:42:54.336153Z",
-     "shell.execute_reply": "2024-02-13T00:42:54.335666Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.886567Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.886294Z",
+     "iopub.status.idle": "2024-02-13T01:08:40.889639Z",
+     "shell.execute_reply": "2024-02-13T01:08:40.889197Z"
     }
    },
    "outputs": [],
@@ -452,10 +452,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:54.338029Z",
-     "iopub.status.busy": "2024-02-13T00:42:54.337850Z",
-     "iopub.status.idle": "2024-02-13T00:42:58.199110Z",
-     "shell.execute_reply": "2024-02-13T00:42:58.198544Z"
+     "iopub.execute_input": "2024-02-13T01:08:40.891643Z",
+     "iopub.status.busy": "2024-02-13T01:08:40.891290Z",
+     "iopub.status.idle": "2024-02-13T01:08:44.750991Z",
+     "shell.execute_reply": "2024-02-13T01:08:44.750358Z"
     }
    },
    "outputs": [
@@ -510,10 +510,10 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:58.201714Z",
-     "iopub.status.busy": "2024-02-13T00:42:58.201490Z",
-     "iopub.status.idle": "2024-02-13T00:42:58.204798Z",
-     "shell.execute_reply": "2024-02-13T00:42:58.204395Z"
+     "iopub.execute_input": "2024-02-13T01:08:44.753844Z",
+     "iopub.status.busy": "2024-02-13T01:08:44.753504Z",
+     "iopub.status.idle": "2024-02-13T01:08:44.757581Z",
+     "shell.execute_reply": "2024-02-13T01:08:44.756535Z"
     }
    },
    "outputs": [],
@@ -535,10 +535,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:58.206779Z",
-     "iopub.status.busy": "2024-02-13T00:42:58.206469Z",
-     "iopub.status.idle": "2024-02-13T00:42:58.209088Z",
-     "shell.execute_reply": "2024-02-13T00:42:58.208664Z"
+     "iopub.execute_input": "2024-02-13T01:08:44.759591Z",
+     "iopub.status.busy": "2024-02-13T01:08:44.759291Z",
+     "iopub.status.idle": "2024-02-13T01:08:44.762187Z",
+     "shell.execute_reply": "2024-02-13T01:08:44.761741Z"
     }
    },
    "outputs": [],
@@ -553,10 +553,10 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:42:58.210925Z",
-     "iopub.status.busy": "2024-02-13T00:42:58.210753Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.504649Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.503987Z"
+     "iopub.execute_input": "2024-02-13T01:08:44.764186Z",
+     "iopub.status.busy": "2024-02-13T01:08:44.763860Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.070931Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.070245Z"
     },
     "scrolled": true
    },
@@ -579,10 +579,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.507863Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.507121Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.515183Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.514651Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.073800Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.073235Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.081363Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.080887Z"
     }
    },
    "outputs": [
@@ -683,10 +683,10 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.517502Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.517046Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.521338Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.520782Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.083578Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.083233Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.087478Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.086756Z"
     }
    },
    "outputs": [],
@@ -700,10 +700,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.523586Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.523250Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.526277Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.525748Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.089472Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.089153Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.092142Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.091597Z"
     }
    },
    "outputs": [
@@ -738,10 +738,10 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.528442Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.528108Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.531026Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.530560Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.094142Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.093964Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.096933Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.096350Z"
     }
    },
    "outputs": [],
@@ -761,10 +761,10 @@
    "execution_count": 17,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.532986Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.532662Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.540215Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.539751Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.099370Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.098865Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.107470Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.106936Z"
     }
    },
    "outputs": [
@@ -889,10 +889,10 @@
    "execution_count": 18,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.542231Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.542041Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.801720Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.801085Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.109868Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.109487Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.340849Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.340332Z"
     },
     "scrolled": true
    },
@@ -931,10 +931,10 @@
    "execution_count": 19,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.805178Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.804254Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.983042Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.982469Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.343564Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.343175Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.521216Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.520698Z"
     },
     "scrolled": true
    },
@@ -967,10 +967,10 @@
    "execution_count": 20,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:43:00.986898Z",
-     "iopub.status.busy": "2024-02-13T00:43:00.985865Z",
-     "iopub.status.idle": "2024-02-13T00:43:00.990975Z",
-     "shell.execute_reply": "2024-02-13T00:43:00.990455Z"
+     "iopub.execute_input": "2024-02-13T01:08:47.523754Z",
+     "iopub.status.busy": "2024-02-13T01:08:47.523385Z",
+     "iopub.status.idle": "2024-02-13T01:08:47.527063Z",
+     "shell.execute_reply": "2024-02-13T01:08:47.526595Z"
     },
     "nbsphinx": "hidden"
    },
diff --git a/master/tutorials/token_classification.html b/master/tutorials/token_classification.html
index 7b265c9b7..af785538b 100644
--- a/master/tutorials/token_classification.html
+++ b/master/tutorials/token_classification.html
@@ -626,7 +626,7 @@ 
    1. Install required dependencies and download data
 
    
 
    ---2024-02-13 00:43:04--  https://data.deepai.org/conll2003.zip
+--2024-02-13 01:08:50--  https://data.deepai.org/conll2003.zip
 Resolving data.deepai.org (data.deepai.org)...
 
    
 
@@ -635,17 +635,9 @@ 
    1. Install required dependencies and download data
 
    
 
    -169.150.236.97, 2400:52e0:1a00::1070:1
-Connecting to data.deepai.org (data.deepai.org)|169.150.236.97|:443... connected.
-HTTP request sent, awaiting response...
-
    
-
-
    
-
    
-
    
-
    
-
    -200 OK
+185.93.1.246, 2400:52e0:1a00::1069:1
+Connecting to data.deepai.org (data.deepai.org)|185.93.1.246|:443... connected.
+HTTP request sent, awaiting response... 200 OK
 Length: 982975 (960K) [application/zip]
 Saving to: ‘conll2003.zip’
    
 
    
@@ -666,25 +658,25 @@ 
    1. Install required dependencies and download data
 
    
 
-
    conll2003.zip       100%[===================&gt;] 959.94K  4.82MB/s    in 0.2s
    
+
    conll2003.zip       100%[===================&gt;] 959.94K  –.-KB/s    in 0.1s
    
 
    
 
    
-
    2024-02-13 00:43:04 (4.82 MB/s) - ‘conll2003.zip’ saved [982975/982975]
    
+
    2024-02-13 01:08:51 (7.92 MB/s) - ‘conll2003.zip’ saved [982975/982975]
    
 
    mkdir: cannot create directory ‘data’: File exists
 </pre>
    
 
    
 
    
-
    conll2003.zip       100%[===================>] 959.94K  4.82MB/s    in 0.2s
    
+
    conll2003.zip       100%[===================>] 959.94K  –.-KB/s    in 0.1s
    
 
    
 
    
-
    2024-02-13 00:43:04 (4.82 MB/s) - ‘conll2003.zip’ saved [982975/982975]
    
+
    2024-02-13 01:08:51 (7.92 MB/s) - ‘conll2003.zip’ saved [982975/982975]
    
 
    mkdir: cannot create directory ‘data’: File exists
 end{sphinxVerbatim}
    
 
    
 
    
-
    conll2003.zip       100%[===================>] 959.94K  4.82MB/s    in 0.2s
    
+
    conll2003.zip       100%[===================>] 959.94K  –.-KB/s    in 0.1s
    
 
    
-
    2024-02-13 00:43:04 (4.82 MB/s) - ‘conll2003.zip’ saved [982975/982975]
    
+
    2024-02-13 01:08:51 (7.92 MB/s) - ‘conll2003.zip’ saved [982975/982975]
    
 
    mkdir: cannot create directory ‘data’: File exists
    
 
    
 
    
@@ -704,9 +696,16 @@ 
    1. Install required dependencies and download data
 
    
 
    ---2024-02-13 00:43:05--  https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz
-Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 52.217.140.217, 52.217.108.172, 52.217.124.193, ...
-Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|52.217.140.217|:443... connected.
+--2024-02-13 01:08:51--  https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz
+Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 52.217.82.132, 54.231.138.209, 3.5.28.120, ...
+Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|52.217.82.132|:443... connected.
+
    
+
    
+
    
+
    
+
    
+
    
+
     HTTP request sent, awaiting response...
 
    
 
    
@@ -730,29 +729,46 @@ 
    1. Install required dependencies and download data
 
    
         if num_classes is not None:
             dataset_information += f", num_classes: {num_classes}"
 
+        if not self.show_all_issues:
+            # Drop any items in the issue_summary that have no issues (any issue detected in data needs to have num_issues > 0)
+            summary = summary.query("num_issues > 0")
+
         if self.show_summary_score:
             return (
                 "Here is a summary of the different kinds of issues found in the data:\n\n"
diff --git a/master/_sources/cleanlab/datalab/guide/custom_issue_manager.rst b/master/_sources/cleanlab/datalab/guide/custom_issue_manager.rst
index ae700dd40..dd7ddcc09 100644
--- a/master/_sources/cleanlab/datalab/guide/custom_issue_manager.rst
+++ b/master/_sources/cleanlab/datalab/guide/custom_issue_manager.rst
@@ -149,10 +149,7 @@ Optionally, you can also add a description of the type of issue this issue manag
 Advanced Issue Check
 ~~~~~~~~~~~~~~~~~~~~
 
-.. note::
-
-    WIP: This section is a work in progress.
-
+There could be different types of issues detected in a dataset. A local issue which affects individual data points in a dataset and can be tracked via `Datalab.issues` dataframe (to see which data points are exhibiting this type of issue). Alternatively, a global issue which affects the overall dataset but is not easily attributable to individual data points (hard to say one data point exhibits the issue but another does not). Even for global issues, we recommend trying to assign a per data point score (and boolean) if possible, see the Non-IID IssueManager as an example of this. Note that a global issue must have num_issues greater than 0 in its `issue_summary`, otherwise it won't show up in `Datalab.report()` by default.
 
 
 Use with Datalab
diff --git a/master/_sources/tutorials/audio.ipynb b/master/_sources/tutorials/audio.ipynb
index b07dc0227..67597bfff 100644
--- a/master/_sources/tutorials/audio.ipynb
+++ b/master/_sources/tutorials/audio.ipynb
@@ -91,7 +91,7 @@
     "os.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\" \n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/datalab/datalab_advanced.ipynb b/master/_sources/tutorials/datalab/datalab_advanced.ipynb
index 20571a1ea..025c61b54 100644
--- a/master/_sources/tutorials/datalab/datalab_advanced.ipynb
+++ b/master/_sources/tutorials/datalab/datalab_advanced.ipynb
@@ -87,7 +87,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]  # TODO: make sure this list is updated\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/datalab/datalab_quickstart.ipynb b/master/_sources/tutorials/datalab/datalab_quickstart.ipynb
index 61a43b50e..51065f955 100644
--- a/master/_sources/tutorials/datalab/datalab_quickstart.ipynb
+++ b/master/_sources/tutorials/datalab/datalab_quickstart.ipynb
@@ -85,7 +85,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]  # TODO: make sure this list is updated\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/datalab/tabular.ipynb b/master/_sources/tutorials/datalab/tabular.ipynb
index af4482d08..b66b50e79 100644
--- a/master/_sources/tutorials/datalab/tabular.ipynb
+++ b/master/_sources/tutorials/datalab/tabular.ipynb
@@ -81,7 +81,7 @@
     "dependencies = [\"cleanlab\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/datalab/text.ipynb b/master/_sources/tutorials/datalab/text.ipynb
index 02f4dec76..0a74b5a7b 100644
--- a/master/_sources/tutorials/datalab/text.ipynb
+++ b/master/_sources/tutorials/datalab/text.ipynb
@@ -90,7 +90,7 @@
     "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\"  # disable parallelism to avoid deadlocks with huggingface\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/dataset_health.ipynb b/master/_sources/tutorials/dataset_health.ipynb
index 19aff9033..3bb5c4145 100644
--- a/master/_sources/tutorials/dataset_health.ipynb
+++ b/master/_sources/tutorials/dataset_health.ipynb
@@ -77,7 +77,7 @@
     "dependencies = [\"cleanlab\", \"requests\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/indepth_overview.ipynb b/master/_sources/tutorials/indepth_overview.ipynb
index 7f9112f94..b7eb5a299 100644
--- a/master/_sources/tutorials/indepth_overview.ipynb
+++ b/master/_sources/tutorials/indepth_overview.ipynb
@@ -62,7 +62,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/multiannotator.ipynb b/master/_sources/tutorials/multiannotator.ipynb
index 1f32339ad..9722072ae 100644
--- a/master/_sources/tutorials/multiannotator.ipynb
+++ b/master/_sources/tutorials/multiannotator.ipynb
@@ -96,7 +96,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/multilabel_classification.ipynb b/master/_sources/tutorials/multilabel_classification.ipynb
index 52d80ca65..9ac24001a 100644
--- a/master/_sources/tutorials/multilabel_classification.ipynb
+++ b/master/_sources/tutorials/multilabel_classification.ipynb
@@ -73,7 +73,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/object_detection.ipynb b/master/_sources/tutorials/object_detection.ipynb
index e52b927e9..746c5edb0 100644
--- a/master/_sources/tutorials/object_detection.ipynb
+++ b/master/_sources/tutorials/object_detection.ipynb
@@ -77,7 +77,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/outliers.ipynb b/master/_sources/tutorials/outliers.ipynb
index 18c042613..7eebfe712 100644
--- a/master/_sources/tutorials/outliers.ipynb
+++ b/master/_sources/tutorials/outliers.ipynb
@@ -119,7 +119,7 @@
     "dependencies = [\"matplotlib\", \"torch\", \"torchvision\", \"timm\", \"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/regression.ipynb b/master/_sources/tutorials/regression.ipynb
index 2590063ad..1a897b9ff 100644
--- a/master/_sources/tutorials/regression.ipynb
+++ b/master/_sources/tutorials/regression.ipynb
@@ -111,7 +111,7 @@
     "dependencies = [\"cleanlab\", \"matplotlib>=3.6.0\", \"datasets\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = \" \".join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/segmentation.ipynb b/master/_sources/tutorials/segmentation.ipynb
index ebdc488a5..2629ae48a 100644
--- a/master/_sources/tutorials/segmentation.ipynb
+++ b/master/_sources/tutorials/segmentation.ipynb
@@ -91,7 +91,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/tabular.ipynb b/master/_sources/tutorials/tabular.ipynb
index 1f4543bf9..1d11b59c5 100644
--- a/master/_sources/tutorials/tabular.ipynb
+++ b/master/_sources/tutorials/tabular.ipynb
@@ -119,7 +119,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/text.ipynb b/master/_sources/tutorials/text.ipynb
index 7b1e3256c..4b392c9c9 100644
--- a/master/_sources/tutorials/text.ipynb
+++ b/master/_sources/tutorials/text.ipynb
@@ -128,7 +128,7 @@
     "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\"  # disable parallelism to avoid deadlocks with huggingface\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/_sources/tutorials/token_classification.ipynb b/master/_sources/tutorials/token_classification.ipynb
index 19a0d0196..757119d64 100644
--- a/master/_sources/tutorials/token_classification.ipynb
+++ b/master/_sources/tutorials/token_classification.ipynb
@@ -95,7 +95,7 @@
     "dependencies = [\"cleanlab\"]\n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
diff --git a/master/cleanlab/datalab/guide/custom_issue_manager.html b/master/cleanlab/datalab/guide/custom_issue_manager.html
index bb3974dcf..8ad79ad9b 100644
--- a/master/cleanlab/datalab/guide/custom_issue_manager.html
+++ b/master/cleanlab/datalab/guide/custom_issue_manager.html
@@ -673,10 +673,7 @@ 
    Implementing IssueManagers
 
    Advanced Issue Check#
    
-
    
-
    Note
    
-
    WIP: This section is a work in progress.
    
-
    
+
    There could be different types of issues detected in a dataset. A local issue which affects individual data points in a dataset and can be tracked via Datalab.issues dataframe (to see which data points are exhibiting this type of issue). Alternatively, a global issue which affects the overall dataset but is not easily attributable to individual data points (hard to say one data point exhibits the issue but another does not). Even for global issues, we recommend trying to assign a per data point score (and boolean) if possible, see the Non-IID IssueManager as an example of this. Note that a global issue must have num_issues greater than 0 in its issue_summary, otherwise it won’t show up in Datalab.report() by default.
    
 
 
 
    
diff --git a/master/searchindex.js b/master/searchindex.js
index f1e84c76c..0f0400536 100644
--- a/master/searchindex.js
+++ b/master/searchindex.js
@@ -1 +1 @@
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"cleanlab/dataset.rst", "cleanlab/experimental/cifar_cnn.rst", "cleanlab/experimental/coteaching.rst", "cleanlab/experimental/index.rst", "cleanlab/experimental/label_issues_batched.rst", "cleanlab/experimental/mnist_pytorch.rst", "cleanlab/filter.rst", "cleanlab/internal/index.rst", "cleanlab/internal/label_quality_utils.rst", "cleanlab/internal/latent_algebra.rst", "cleanlab/internal/multiannotator_utils.rst", "cleanlab/internal/multilabel_scorer.rst", "cleanlab/internal/multilabel_utils.rst", "cleanlab/internal/outlier.rst", "cleanlab/internal/token_classification_utils.rst", "cleanlab/internal/util.rst", "cleanlab/internal/validation.rst", "cleanlab/models/fasttext.rst", "cleanlab/models/index.rst", "cleanlab/models/keras.rst", "cleanlab/multiannotator.rst", "cleanlab/multilabel_classification/dataset.rst", "cleanlab/multilabel_classification/filter.rst", "cleanlab/multilabel_classification/index.rst", "cleanlab/multilabel_classification/rank.rst", 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Use cleanlab to find issues in your dataset": [[80, "4.-Use-cleanlab-to-find-issues-in-your-dataset"]], "Non-IID issues (data drift)": [[80, "Non-IID-issues-(data-drift)"]], "Find Dataset-level Issues for Dataset Curation": [[81, "Find-Dataset-level-Issues-for-Dataset-Curation"]], "Install dependencies and import them": [[81, "Install-dependencies-and-import-them"], [84, "Install-dependencies-and-import-them"]], "Fetch the data (can skip these details)": [[81, "Fetch-the-data-(can-skip-these-details)"]], "Start of tutorial: Evaluate the health of 8 popular datasets": [[81, "Start-of-tutorial:-Evaluate-the-health-of-8-popular-datasets"]], "FAQ": [[82, "FAQ"]], "What data can cleanlab detect issues in?": [[82, "What-data-can-cleanlab-detect-issues-in?"]], "How do I format classification labels for cleanlab?": [[82, "How-do-I-format-classification-labels-for-cleanlab?"]], "How do I infer the correct labels for examples cleanlab has flagged?": [[82, "How-do-I-infer-the-correct-labels-for-examples-cleanlab-has-flagged?"]], "How should I handle label errors in train vs. test data?": [[82, "How-should-I-handle-label-errors-in-train-vs.-test-data?"]], "How can I find label issues in big datasets with limited memory?": [[82, "How-can-I-find-label-issues-in-big-datasets-with-limited-memory?"]], "Why isn\u2019t CleanLearning working for me?": [[82, "Why-isn\u2019t-CleanLearning-working-for-me?"]], "How can I use different models for data cleaning vs. final training in CleanLearning?": [[82, "How-can-I-use-different-models-for-data-cleaning-vs.-final-training-in-CleanLearning?"]], "How do I hyperparameter tune only the final model trained (and not the one finding label issues) in CleanLearning?": [[82, "How-do-I-hyperparameter-tune-only-the-final-model-trained-(and-not-the-one-finding-label-issues)-in-CleanLearning?"]], "Why does regression.learn.CleanLearning take so long?": [[82, "Why-does-regression.learn.CleanLearning-take-so-long?"]], "How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?": [[82, "How-do-I-specify-pre-computed-data-slices/clusters-when-detecting-the-Underperforming-Group-Issue?"]], "How to handle near-duplicate data identified by cleanlab?": [[82, "How-to-handle-near-duplicate-data-identified-by-cleanlab?"]], "What ML models should I run cleanlab with? How do I fix the issues cleanlab has identified?": [[82, "What-ML-models-should-I-run-cleanlab-with?-How-do-I-fix-the-issues-cleanlab-has-identified?"]], "What license is cleanlab open-sourced under?": [[82, "What-license-is-cleanlab-open-sourced-under?"]], "Can\u2019t find an answer to your question?": [[82, "Can't-find-an-answer-to-your-question?"]], "Image Classification with PyTorch and Cleanlab": [[83, "Image-Classification-with-PyTorch-and-Cleanlab"]], "2. Fetch and normalize the Fashion-MNIST dataset": [[83, "2.-Fetch-and-normalize-the-Fashion-MNIST-dataset"]], "3. Define a classification model": [[83, "3.-Define-a-classification-model"]], "4. Prepare the dataset for K-fold cross-validation": [[83, "4.-Prepare-the-dataset-for-K-fold-cross-validation"]], "5. Compute out-of-sample predicted probabilities and feature embeddings": [[83, "5.-Compute-out-of-sample-predicted-probabilities-and-feature-embeddings"]], "7. Use cleanlab to find issues": [[83, "7.-Use-cleanlab-to-find-issues"]], "View report": [[83, "View-report"]], "View most likely examples with label errors": [[83, "View-most-likely-examples-with-label-errors"]], "View most severe outliers": [[83, "View-most-severe-outliers"]], "View sets of near duplicate images": [[83, "View-sets-of-near-duplicate-images"]], "Dark images": [[83, "Dark-images"]], "View top examples of dark images": [[83, "View-top-examples-of-dark-images"]], "Low information images": [[83, "Low-information-images"]], "The Workflows of Data-centric AI for Classification with Noisy Labels": [[84, "The-Workflows-of-Data-centric-AI-for-Classification-with-Noisy-Labels"]], "Create the data (can skip these details)": [[84, "Create-the-data-(can-skip-these-details)"]], "Workflow 1: Use Datalab to detect many types of issues": [[84, "Workflow-1:-Use-Datalab-to-detect-many-types-of-issues"]], "Workflow 2: Use CleanLearning for more robust Machine Learning": [[84, "Workflow-2:-Use-CleanLearning-for-more-robust-Machine-Learning"]], "Clean Learning = Machine Learning with cleaned data": [[84, "Clean-Learning-=-Machine-Learning-with-cleaned-data"]], "Workflow 3: Use CleanLearning to find_label_issues in one line of code": [[84, "Workflow-3:-Use-CleanLearning-to-find_label_issues-in-one-line-of-code"]], "Visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[84, "Visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 4: Use cleanlab to find dataset-level and class-level issues": [[84, "Workflow-4:-Use-cleanlab-to-find-dataset-level-and-class-level-issues"]], "Now, let\u2019s see what happens if we merge classes \u201cseafoam green\u201d and \u201cyellow\u201d": [[84, "Now,-let's-see-what-happens-if-we-merge-classes-%22seafoam-green%22-and-%22yellow%22"]], "Workflow 5: Clean your test set too if you\u2019re doing ML with noisy labels!": [[84, "Workflow-5:-Clean-your-test-set-too-if-you're-doing-ML-with-noisy-labels!"]], "Workflow 6: One score to rule them all \u2013 use cleanlab\u2019s overall dataset health score": [[84, "Workflow-6:-One-score-to-rule-them-all----use-cleanlab's-overall-dataset-health-score"]], "How accurate is this dataset health score?": [[84, "How-accurate-is-this-dataset-health-score?"]], "Workflow(s) 7: Use count, rank, filter modules directly": [[84, "Workflow(s)-7:-Use-count,-rank,-filter-modules-directly"]], "Workflow 7.1 (count): Fully characterize label noise (noise matrix, joint, prior of true labels, \u2026)": [[84, "Workflow-7.1-(count):-Fully-characterize-label-noise-(noise-matrix,-joint,-prior-of-true-labels,-...)"]], "Use cleanlab to estimate and visualize the joint distribution of label noise and noise matrix of label flipping rates:": [[84, "Use-cleanlab-to-estimate-and-visualize-the-joint-distribution-of-label-noise-and-noise-matrix-of-label-flipping-rates:"]], "Workflow 7.2 (filter): Find label issues for any dataset and any model in one line of code": [[84, "Workflow-7.2-(filter):-Find-label-issues-for-any-dataset-and-any-model-in-one-line-of-code"]], "Again, we can visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[84, "Again,-we-can-visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 7.2 supports lots of methods to find_label_issues() via the filter_by parameter.": [[84, "Workflow-7.2-supports-lots-of-methods-to-find_label_issues()-via-the-filter_by-parameter."]], "Workflow 7.3 (rank): Automatically rank every example by a unique label quality score. Find errors using cleanlab.count.num_label_issues as a threshold.": [[84, "Workflow-7.3-(rank):-Automatically-rank-every-example-by-a-unique-label-quality-score.-Find-errors-using-cleanlab.count.num_label_issues-as-a-threshold."]], "Again, we can visualize the label issues found to see if Cleanlab works.": [[84, "Again,-we-can-visualize-the-label-issues-found-to-see-if-Cleanlab-works."]], "Not sure when to use Workflow 7.2 or 7.3 to find label issues?": [[84, "Not-sure-when-to-use-Workflow-7.2-or-7.3-to-find-label-issues?"]], "Workflow 8: Ensembling label quality scores from multiple predictors": [[84, "Workflow-8:-Ensembling-label-quality-scores-from-multiple-predictors"]], "Tutorials": [[85, "tutorials"]], "Estimate Consensus and Annotator Quality for Data Labeled by Multiple Annotators": [[86, "Estimate-Consensus-and-Annotator-Quality-for-Data-Labeled-by-Multiple-Annotators"]], "2. Create the data (can skip these details)": [[86, "2.-Create-the-data-(can-skip-these-details)"]], "3. Get initial consensus labels via majority vote and compute out-of-sample predicted probabilities": [[86, "3.-Get-initial-consensus-labels-via-majority-vote-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to get better consensus labels and other statistics": [[86, "4.-Use-cleanlab-to-get-better-consensus-labels-and-other-statistics"]], "Comparing improved consensus labels": [[86, "Comparing-improved-consensus-labels"]], "Inspecting consensus quality scores to find potential consensus label errors": [[86, "Inspecting-consensus-quality-scores-to-find-potential-consensus-label-errors"]], "5. Retrain model using improved consensus labels": [[86, "5.-Retrain-model-using-improved-consensus-labels"]], "Further improvements": [[86, "Further-improvements"]], "How does cleanlab.multiannotator work?": [[86, "How-does-cleanlab.multiannotator-work?"]], "Find Label Errors in Multi-Label Classification Datasets": [[87, "Find-Label-Errors-in-Multi-Label-Classification-Datasets"]], "1. Install required dependencies and get dataset": [[87, "1.-Install-required-dependencies-and-get-dataset"]], "2. Format data, labels, and model predictions": [[87, "2.-Format-data,-labels,-and-model-predictions"], [88, "2.-Format-data,-labels,-and-model-predictions"]], "3. Use cleanlab to find label issues": [[87, "3.-Use-cleanlab-to-find-label-issues"], [88, "3.-Use-cleanlab-to-find-label-issues"], [92, "3.-Use-cleanlab-to-find-label-issues"], [95, "3.-Use-cleanlab-to-find-label-issues"]], "Label quality scores": [[87, "Label-quality-scores"]], "Data issues beyond mislabeling (outliers, duplicates, drift, \u2026)": [[87, "Data-issues-beyond-mislabeling-(outliers,-duplicates,-drift,-...)"]], "How to format labels given as a one-hot (multi-hot) binary matrix?": [[87, "How-to-format-labels-given-as-a-one-hot-(multi-hot)-binary-matrix?"]], "Estimate label issues without Datalab": [[87, "Estimate-label-issues-without-Datalab"]], "Application to Real Data": [[87, "Application-to-Real-Data"]], "Finding Label Errors in Object Detection Datasets": [[88, "Finding-Label-Errors-in-Object-Detection-Datasets"]], "1. Install required dependencies and download data": [[88, "1.-Install-required-dependencies-and-download-data"], [92, "1.-Install-required-dependencies-and-download-data"], [95, "1.-Install-required-dependencies-and-download-data"]], "Get label quality scores": [[88, "Get-label-quality-scores"], [92, "Get-label-quality-scores"]], "4. Use ObjectLab to visualize label issues": [[88, "4.-Use-ObjectLab-to-visualize-label-issues"]], "Different kinds of label issues identified by ObjectLab": [[88, "Different-kinds-of-label-issues-identified-by-ObjectLab"]], "Other uses of visualize": [[88, "Other-uses-of-visualize"]], "Exploratory data analysis": [[88, "Exploratory-data-analysis"]], "Detect Outliers with Cleanlab and PyTorch Image Models (timm)": [[89, "Detect-Outliers-with-Cleanlab-and-PyTorch-Image-Models-(timm)"]], "1. Install the required dependencies": [[89, "1.-Install-the-required-dependencies"]], "2. Pre-process the Cifar10 dataset": [[89, "2.-Pre-process-the-Cifar10-dataset"]], "Visualize some of the training and test examples": [[89, "Visualize-some-of-the-training-and-test-examples"]], "3. Use cleanlab and feature embeddings to find outliers in the data": [[89, "3.-Use-cleanlab-and-feature-embeddings-to-find-outliers-in-the-data"]], "4. Use cleanlab and pred_probs to find outliers in the data": [[89, "4.-Use-cleanlab-and-pred_probs-to-find-outliers-in-the-data"]], "Computing Out-of-Sample Predicted Probabilities with Cross-Validation": [[90, "computing-out-of-sample-predicted-probabilities-with-cross-validation"]], "Out-of-sample predicted probabilities?": [[90, "out-of-sample-predicted-probabilities"]], "What is K-fold cross-validation?": [[90, "what-is-k-fold-cross-validation"]], "Find Noisy Labels in Regression Datasets": [[91, "Find-Noisy-Labels-in-Regression-Datasets"]], "3. Define a regression model and use cleanlab to find potential label errors": [[91, "3.-Define-a-regression-model-and-use-cleanlab-to-find-potential-label-errors"]], "4. Train a more robust model from noisy labels": [[91, "4.-Train-a-more-robust-model-from-noisy-labels"], [94, "4.-Train-a-more-robust-model-from-noisy-labels"]], "5. Other ways to find noisy labels in regression datasets": [[91, "5.-Other-ways-to-find-noisy-labels-in-regression-datasets"]], "Find Label Errors in Semantic Segmentation Datasets": [[92, "Find-Label-Errors-in-Semantic-Segmentation-Datasets"]], "2. Get data, labels, and pred_probs": [[92, "2.-Get-data,-labels,-and-pred_probs"], [95, "2.-Get-data,-labels,-and-pred_probs"]], "Visualize top label issues": [[92, "Visualize-top-label-issues"]], "Classes which are commonly mislabeled overall": [[92, "Classes-which-are-commonly-mislabeled-overall"]], "Focusing on one specific class": [[92, "Focusing-on-one-specific-class"]], "Classification with Tabular Data using Scikit-Learn and Cleanlab": [[93, "Classification-with-Tabular-Data-using-Scikit-Learn-and-Cleanlab"]], "4. Use cleanlab to find label issues": [[93, "4.-Use-cleanlab-to-find-label-issues"]], "5. Train a more robust model from noisy labels": [[93, "5.-Train-a-more-robust-model-from-noisy-labels"]], "Text Classification with Noisy Labels": [[94, "Text-Classification-with-Noisy-Labels"]], "3. Define a classification model and use cleanlab to find potential label errors": [[94, "3.-Define-a-classification-model-and-use-cleanlab-to-find-potential-label-errors"]], "Find Label Errors in Token Classification (Text) Datasets": [[95, "Find-Label-Errors-in-Token-Classification-(Text)-Datasets"]], "Most common word-level token mislabels": [[95, "Most-common-word-level-token-mislabels"]], "Find sentences containing a particular mislabeled word": [[95, "Find-sentences-containing-a-particular-mislabeled-word"]], "Sentence label quality score": [[95, "Sentence-label-quality-score"]], "How does cleanlab.token_classification work?": [[95, "How-does-cleanlab.token_classification-work?"]]}, "indexentries": {"cleanlab.benchmarking": [[0, "module-cleanlab.benchmarking"]], "module": [[0, "module-cleanlab.benchmarking"], [1, "module-cleanlab.benchmarking.noise_generation"], [2, "module-cleanlab.classification"], [3, "module-cleanlab.count"], [4, "module-cleanlab.datalab.datalab"], [9, "module-cleanlab.datalab"], [10, "module-cleanlab.datalab.internal.data"], [11, "module-cleanlab.datalab.internal.data_issues"], [12, "module-cleanlab.datalab.internal.issue_manager_factory"], [13, "module-cleanlab.datalab.internal"], [14, "module-cleanlab.datalab.internal.issue_finder"], [16, "module-cleanlab.datalab.internal.issue_manager.data_valuation"], [17, "module-cleanlab.datalab.internal.issue_manager.duplicate"], [18, "module-cleanlab.datalab.internal.issue_manager.imbalance"], [20, "module-cleanlab.datalab.internal.issue_manager.issue_manager"], [21, "module-cleanlab.datalab.internal.issue_manager.label"], [22, "module-cleanlab.datalab.internal.issue_manager.noniid"], [23, "module-cleanlab.datalab.internal.issue_manager.null"], [24, "module-cleanlab.datalab.internal.issue_manager.outlier"], [26, "module-cleanlab.datalab.internal.issue_manager.regression.label"], [27, "module-cleanlab.datalab.internal.issue_manager.underperforming_group"], [28, "module-cleanlab.datalab.internal.report"], [29, "module-cleanlab.datalab.internal.task"], [31, "module-cleanlab.dataset"], [32, "module-cleanlab.experimental.cifar_cnn"], [33, "module-cleanlab.experimental.coteaching"], [34, "module-cleanlab.experimental"], [35, "module-cleanlab.experimental.label_issues_batched"], [36, "module-cleanlab.experimental.mnist_pytorch"], [37, "module-cleanlab.filter"], [38, "module-cleanlab.internal"], [39, "module-cleanlab.internal.label_quality_utils"], [40, "module-cleanlab.internal.latent_algebra"], [41, "module-cleanlab.internal.multiannotator_utils"], [42, "module-cleanlab.internal.multilabel_scorer"], [43, "module-cleanlab.internal.multilabel_utils"], [44, "module-cleanlab.internal.outlier"], [45, "module-cleanlab.internal.token_classification_utils"], [46, "module-cleanlab.internal.util"], [47, "module-cleanlab.internal.validation"], [49, "module-cleanlab.models"], [50, "module-cleanlab.models.keras"], [51, "module-cleanlab.multiannotator"], [52, 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"cleanlab.datalab.internal.data.DatasetDictError.add_note"]], "add_note() (cleanlab.datalab.internal.data.datasetloaderror method)": [[10, "cleanlab.datalab.internal.data.DatasetLoadError.add_note"]], "args (cleanlab.datalab.internal.data.dataformaterror attribute)": [[10, "cleanlab.datalab.internal.data.DataFormatError.args"]], "args (cleanlab.datalab.internal.data.datasetdicterror attribute)": [[10, "cleanlab.datalab.internal.data.DatasetDictError.args"]], "args (cleanlab.datalab.internal.data.datasetloaderror attribute)": [[10, "cleanlab.datalab.internal.data.DatasetLoadError.args"]], "class_names (cleanlab.datalab.internal.data.data property)": [[10, "cleanlab.datalab.internal.data.Data.class_names"]], "class_names (cleanlab.datalab.internal.data.label property)": [[10, "cleanlab.datalab.internal.data.Label.class_names"]], "class_names (cleanlab.datalab.internal.data.multiclass property)": [[10, "cleanlab.datalab.internal.data.MultiClass.class_names"]], "class_names (cleanlab.datalab.internal.data.multilabel property)": [[10, "cleanlab.datalab.internal.data.MultiLabel.class_names"]], "cleanlab.datalab.internal.data": [[10, "module-cleanlab.datalab.internal.data"]], "has_labels (cleanlab.datalab.internal.data.data property)": [[10, "cleanlab.datalab.internal.data.Data.has_labels"]], "is_available (cleanlab.datalab.internal.data.label property)": [[10, "cleanlab.datalab.internal.data.Label.is_available"]], "is_available (cleanlab.datalab.internal.data.multiclass property)": [[10, "cleanlab.datalab.internal.data.MultiClass.is_available"]], "is_available (cleanlab.datalab.internal.data.multilabel property)": [[10, "cleanlab.datalab.internal.data.MultiLabel.is_available"]], "with_traceback() (cleanlab.datalab.internal.data.dataformaterror method)": [[10, "cleanlab.datalab.internal.data.DataFormatError.with_traceback"]], "with_traceback() (cleanlab.datalab.internal.data.datasetdicterror method)": [[10, "cleanlab.datalab.internal.data.DatasetDictError.with_traceback"]], "with_traceback() (cleanlab.datalab.internal.data.datasetloaderror method)": [[10, "cleanlab.datalab.internal.data.DatasetLoadError.with_traceback"]], "dataissues (class in cleanlab.datalab.internal.data_issues)": [[11, "cleanlab.datalab.internal.data_issues.DataIssues"]], "cleanlab.datalab.internal.data_issues": [[11, "module-cleanlab.datalab.internal.data_issues"]], "collect_issues_from_imagelab() (cleanlab.datalab.internal.data_issues.dataissues method)": [[11, "cleanlab.datalab.internal.data_issues.DataIssues.collect_issues_from_imagelab"]], "collect_issues_from_issue_manager() (cleanlab.datalab.internal.data_issues.dataissues method)": [[11, "cleanlab.datalab.internal.data_issues.DataIssues.collect_issues_from_issue_manager"]], "collect_statistics() (cleanlab.datalab.internal.data_issues.dataissues method)": [[11, "cleanlab.datalab.internal.data_issues.DataIssues.collect_statistics"]], "get_data_statistics() (in 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"set_health_score() (cleanlab.datalab.internal.data_issues.dataissues method)": [[11, "cleanlab.datalab.internal.data_issues.DataIssues.set_health_score"]], "statistics (cleanlab.datalab.internal.data_issues.dataissues property)": [[11, "cleanlab.datalab.internal.data_issues.DataIssues.statistics"]], "registry (in module cleanlab.datalab.internal.issue_manager_factory)": [[12, "cleanlab.datalab.internal.issue_manager_factory.REGISTRY"]], "cleanlab.datalab.internal.issue_manager_factory": [[12, "module-cleanlab.datalab.internal.issue_manager_factory"]], "list_default_issue_types() (in module cleanlab.datalab.internal.issue_manager_factory)": [[12, "cleanlab.datalab.internal.issue_manager_factory.list_default_issue_types"]], "list_possible_issue_types() (in module cleanlab.datalab.internal.issue_manager_factory)": [[12, "cleanlab.datalab.internal.issue_manager_factory.list_possible_issue_types"]], "register() (in module cleanlab.datalab.internal.issue_manager_factory)": [[12, "cleanlab.datalab.internal.issue_manager_factory.register"]], "cleanlab.datalab.internal": [[13, "module-cleanlab.datalab.internal"]], "issuefinder (class in cleanlab.datalab.internal.issue_finder)": [[14, "cleanlab.datalab.internal.issue_finder.IssueFinder"]], "cleanlab.datalab.internal.issue_finder": [[14, "module-cleanlab.datalab.internal.issue_finder"]], "find_issues() (cleanlab.datalab.internal.issue_finder.issuefinder method)": [[14, "cleanlab.datalab.internal.issue_finder.IssueFinder.find_issues"]], "get_available_issue_types() (cleanlab.datalab.internal.issue_finder.issuefinder method)": [[14, "cleanlab.datalab.internal.issue_finder.IssueFinder.get_available_issue_types"]], "default_threshold (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.DEFAULT_THRESHOLD"]], "datavaluationissuemanager (class in cleanlab.datalab.internal.issue_manager.data_valuation)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager"]], "cleanlab.datalab.internal.issue_manager.data_valuation": [[16, "module-cleanlab.datalab.internal.issue_manager.data_valuation"]], "collect_info() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager method)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager method)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager class method)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager class method)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.verbosity_levels"]], "nearduplicateissuemanager (class in cleanlab.datalab.internal.issue_manager.duplicate)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager"]], "cleanlab.datalab.internal.issue_manager.duplicate": [[17, "module-cleanlab.datalab.internal.issue_manager.duplicate"]], "collect_info() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager method)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager method)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager class method)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.make_summary"]], "near_duplicate_sets (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.near_duplicate_sets"]], "report() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager class method)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.verbosity_levels"]], "classimbalanceissuemanager (class in cleanlab.datalab.internal.issue_manager.imbalance)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager"]], "cleanlab.datalab.internal.issue_manager.imbalance": [[18, "module-cleanlab.datalab.internal.issue_manager.imbalance"]], "collect_info() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager method)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager method)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager class method)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager class method)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[18, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.verbosity_levels"]], "issuemanager (class in cleanlab.datalab.internal.issue_manager.issue_manager)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager"]], "cleanlab.datalab.internal.issue_manager.issue_manager": [[20, "module-cleanlab.datalab.internal.issue_manager.issue_manager"]], "collect_info() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager method)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager method)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager class method)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager class method)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[20, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.verbosity_levels"]], "labelissuemanager (class in cleanlab.datalab.internal.issue_manager.label)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.label": [[21, "module-cleanlab.datalab.internal.issue_manager.label"]], "collect_info() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager method)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager method)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.find_issues"]], "get_health_summary() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager method)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.get_health_summary"]], "health_summary_parameters (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.health_summary_parameters"]], "info (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager class method)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager class method)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.verbosity_levels"]], "noniidissuemanager (class in cleanlab.datalab.internal.issue_manager.noniid)": [[22, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager"]], "cleanlab.datalab.internal.issue_manager.noniid": [[22, "module-cleanlab.datalab.internal.issue_manager.noniid"]], "collect_info() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager method)": [[22, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager method)": [[22, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager class method)": [[22, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager class method)": [[22, 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"task"]], "dataset": [[31, "module-cleanlab.dataset"], [52, "module-cleanlab.multilabel_classification.dataset"]], "cifar_cnn": [[32, "module-cleanlab.experimental.cifar_cnn"]], "coteaching": [[33, "module-cleanlab.experimental.coteaching"]], "experimental": [[34, "experimental"]], "label_issues_batched": [[35, "module-cleanlab.experimental.label_issues_batched"]], "mnist_pytorch": [[36, "module-cleanlab.experimental.mnist_pytorch"]], "filter": [[37, "module-cleanlab.filter"], [53, "module-cleanlab.multilabel_classification.filter"], [56, "filter"], [65, "filter"], [69, "module-cleanlab.token_classification.filter"]], "label_quality_utils": [[39, "module-cleanlab.internal.label_quality_utils"]], "latent_algebra": [[40, "module-cleanlab.internal.latent_algebra"]], "multiannotator_utils": [[41, "module-cleanlab.internal.multiannotator_utils"]], "multilabel_scorer": [[42, "module-cleanlab.internal.multilabel_scorer"]], "multilabel_utils": [[43, "module-cleanlab.internal.multilabel_utils"]], "token_classification_utils": [[45, "module-cleanlab.internal.token_classification_utils"]], "util": [[46, "module-cleanlab.internal.util"]], "validation": [[47, "module-cleanlab.internal.validation"]], "fasttext": [[48, "fasttext"]], "models": [[49, "models"]], "keras": [[50, "module-cleanlab.models.keras"]], "multiannotator": [[51, "module-cleanlab.multiannotator"]], "multilabel_classification": [[54, "multilabel-classification"]], "rank": [[55, "module-cleanlab.multilabel_classification.rank"], [58, "module-cleanlab.object_detection.rank"], [61, "module-cleanlab.rank"], [67, "module-cleanlab.segmentation.rank"], [71, "module-cleanlab.token_classification.rank"]], "object_detection": [[57, "object-detection"]], "summary": [[59, "summary"], [68, "module-cleanlab.segmentation.summary"], [72, "module-cleanlab.token_classification.summary"]], "regression.learn": [[63, "module-cleanlab.regression.learn"]], "regression.rank": [[64, "module-cleanlab.regression.rank"]], "segmentation": [[66, "segmentation"]], "token_classification": [[70, "token-classification"]], "cleanlab open-source documentation": [[73, "cleanlab-open-source-documentation"]], "Quickstart": [[73, "quickstart"]], "1. Install cleanlab": [[73, "install-cleanlab"]], "2. Find common issues in your data": [[73, "find-common-issues-in-your-data"]], "3. Handle label errors and train robust models with noisy labels": [[73, "handle-label-errors-and-train-robust-models-with-noisy-labels"]], "4. Dataset curation: fix dataset-level issues": [[73, "dataset-curation-fix-dataset-level-issues"]], "5. Improve your data via many other techniques": [[73, "improve-your-data-via-many-other-techniques"]], "Contributing": [[73, "contributing"]], "Easy Mode": [[73, "easy-mode"], [79, "Easy-Mode"], [80, "Easy-Mode"], [83, "Easy-Mode"]], "How to migrate to versions >= 2.0.0 from pre 1.0.1": [[74, "how-to-migrate-to-versions-2-0-0-from-pre-1-0-1"]], "Function and class name changes": [[74, "function-and-class-name-changes"]], "Module name changes": [[74, "module-name-changes"]], "New modules": [[74, "new-modules"]], "Removed modules": [[74, "removed-modules"]], "Common argument and variable name changes": [[74, "common-argument-and-variable-name-changes"]], "Audio Classification with SpeechBrain and Cleanlab": [[75, "Audio-Classification-with-SpeechBrain-and-Cleanlab"]], "1. Install dependencies and import them": [[75, "1.-Install-dependencies-and-import-them"]], "2. Load the data": [[75, "2.-Load-the-data"]], "3. Use pre-trained SpeechBrain model to featurize audio": [[75, "3.-Use-pre-trained-SpeechBrain-model-to-featurize-audio"]], "4. Fit linear model and compute out-of-sample predicted probabilities": [[75, "4.-Fit-linear-model-and-compute-out-of-sample-predicted-probabilities"]], "5. Use cleanlab to find label issues": [[75, "5.-Use-cleanlab-to-find-label-issues"], [79, "5.-Use-cleanlab-to-find-label-issues"]], "Datalab: Advanced workflows to audit your data": [[76, "Datalab:-Advanced-workflows-to-audit-your-data"]], "Install and import required dependencies": [[76, "Install-and-import-required-dependencies"]], "Create and load the data": [[76, "Create-and-load-the-data"]], "Get out-of-sample predicted probabilities from a classifier": [[76, "Get-out-of-sample-predicted-probabilities-from-a-classifier"]], "Instantiate Datalab object": [[76, "Instantiate-Datalab-object"]], "Functionality 1: Incremental issue search": [[76, "Functionality-1:-Incremental-issue-search"]], "Functionality 2: Specifying nondefault arguments": [[76, "Functionality-2:-Specifying-nondefault-arguments"]], "Functionality 3: Save and load Datalab objects": [[76, "Functionality-3:-Save-and-load-Datalab-objects"]], "Functionality 4: Adding a custom IssueManager": [[76, "Functionality-4:-Adding-a-custom-IssueManager"]], "Datalab: A unified audit to detect all kinds of issues in data and labels": [[77, "Datalab:-A-unified-audit-to-detect-all-kinds-of-issues-in-data-and-labels"]], "1. Install and import required dependencies": [[77, "1.-Install-and-import-required-dependencies"], [83, "1.-Install-and-import-required-dependencies"], [86, "1.-Install-and-import-required-dependencies"]], "2. Create and load the data (can skip these details)": [[77, "2.-Create-and-load-the-data-(can-skip-these-details)"]], "3. Get out-of-sample predicted probabilities from a classifier": [[77, "3.-Get-out-of-sample-predicted-probabilities-from-a-classifier"]], "4. Use Datalab to find issues in the dataset": [[77, "4.-Use-Datalab-to-find-issues-in-the-dataset"]], "5. Learn more about the issues in your dataset": [[77, "5.-Learn-more-about-the-issues-in-your-dataset"]], "Get additional information": [[77, "Get-additional-information"]], "Near duplicate issues": [[77, "Near-duplicate-issues"], [83, "Near-duplicate-issues"]], "Datalab Tutorials": [[78, "datalab-tutorials"]], "Detecting Issues in Tabular Data\u00a0(Numeric/Categorical columns) with Datalab": [[79, "Detecting-Issues-in-Tabular-Data\u00a0(Numeric/Categorical-columns)-with-Datalab"]], "1. Install required dependencies": [[79, "1.-Install-required-dependencies"], [80, "1.-Install-required-dependencies"], [91, "1.-Install-required-dependencies"], [93, "1.-Install-required-dependencies"], [94, "1.-Install-required-dependencies"]], "2. Load and process the data": [[79, "2.-Load-and-process-the-data"], [91, "2.-Load-and-process-the-data"], [93, "2.-Load-and-process-the-data"]], "3. Select a classification model and compute out-of-sample predicted probabilities": [[79, "3.-Select-a-classification-model-and-compute-out-of-sample-predicted-probabilities"], [93, "3.-Select-a-classification-model-and-compute-out-of-sample-predicted-probabilities"]], "4. Construct K nearest neighbours graph": [[79, "4.-Construct-K-nearest-neighbours-graph"]], "Label issues": [[79, "Label-issues"], [80, "Label-issues"], [83, "Label-issues"]], "Outlier issues": [[79, "Outlier-issues"], [80, "Outlier-issues"], [83, "Outlier-issues"]], "Near-duplicate issues": [[79, "Near-duplicate-issues"], [80, "Near-duplicate-issues"]], "Detecting Issues in a Text Dataset with Datalab": [[80, "Detecting-Issues-in-a-Text-Dataset-with-Datalab"]], "2. Load and format the text dataset": [[80, "2.-Load-and-format-the-text-dataset"], [94, "2.-Load-and-format-the-text-dataset"]], "3. Define a classification model and compute out-of-sample predicted probabilities": [[80, "3.-Define-a-classification-model-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to find issues in your dataset": [[80, "4.-Use-cleanlab-to-find-issues-in-your-dataset"]], "Non-IID issues (data drift)": [[80, "Non-IID-issues-(data-drift)"]], "Find Dataset-level Issues for Dataset Curation": [[81, "Find-Dataset-level-Issues-for-Dataset-Curation"]], "Install dependencies and import them": [[81, "Install-dependencies-and-import-them"], [84, "Install-dependencies-and-import-them"]], "Fetch the data (can skip these details)": [[81, "Fetch-the-data-(can-skip-these-details)"]], "Start of tutorial: Evaluate the health of 8 popular datasets": [[81, "Start-of-tutorial:-Evaluate-the-health-of-8-popular-datasets"]], "FAQ": [[82, "FAQ"]], "What data can cleanlab detect issues in?": [[82, "What-data-can-cleanlab-detect-issues-in?"]], "How do I format classification labels for cleanlab?": [[82, "How-do-I-format-classification-labels-for-cleanlab?"]], "How do I infer the correct labels for examples cleanlab has flagged?": [[82, "How-do-I-infer-the-correct-labels-for-examples-cleanlab-has-flagged?"]], "How should I handle label errors in train vs. test data?": [[82, "How-should-I-handle-label-errors-in-train-vs.-test-data?"]], "How can I find label issues in big datasets with limited memory?": [[82, "How-can-I-find-label-issues-in-big-datasets-with-limited-memory?"]], "Why isn\u2019t CleanLearning working for me?": [[82, "Why-isn\u2019t-CleanLearning-working-for-me?"]], "How can I use different models for data cleaning vs. final training in CleanLearning?": [[82, "How-can-I-use-different-models-for-data-cleaning-vs.-final-training-in-CleanLearning?"]], "How do I hyperparameter tune only the final model trained (and not the one finding label issues) in CleanLearning?": [[82, "How-do-I-hyperparameter-tune-only-the-final-model-trained-(and-not-the-one-finding-label-issues)-in-CleanLearning?"]], "Why does regression.learn.CleanLearning take so long?": [[82, "Why-does-regression.learn.CleanLearning-take-so-long?"]], "How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?": [[82, "How-do-I-specify-pre-computed-data-slices/clusters-when-detecting-the-Underperforming-Group-Issue?"]], "How to handle near-duplicate data identified by cleanlab?": [[82, "How-to-handle-near-duplicate-data-identified-by-cleanlab?"]], "What ML models should I run cleanlab with? How do I fix the issues cleanlab has identified?": [[82, "What-ML-models-should-I-run-cleanlab-with?-How-do-I-fix-the-issues-cleanlab-has-identified?"]], "What license is cleanlab open-sourced under?": [[82, "What-license-is-cleanlab-open-sourced-under?"]], "Can\u2019t find an answer to your question?": [[82, "Can't-find-an-answer-to-your-question?"]], "Image Classification with PyTorch and Cleanlab": [[83, "Image-Classification-with-PyTorch-and-Cleanlab"]], "2. Fetch and normalize the Fashion-MNIST dataset": [[83, "2.-Fetch-and-normalize-the-Fashion-MNIST-dataset"]], "3. Define a classification model": [[83, "3.-Define-a-classification-model"]], "4. Prepare the dataset for K-fold cross-validation": [[83, "4.-Prepare-the-dataset-for-K-fold-cross-validation"]], "5. Compute out-of-sample predicted probabilities and feature embeddings": [[83, "5.-Compute-out-of-sample-predicted-probabilities-and-feature-embeddings"]], "7. Use cleanlab to find issues": [[83, "7.-Use-cleanlab-to-find-issues"]], "View report": [[83, "View-report"]], "View most likely examples with label errors": [[83, "View-most-likely-examples-with-label-errors"]], "View most severe outliers": [[83, "View-most-severe-outliers"]], "View sets of near duplicate images": [[83, "View-sets-of-near-duplicate-images"]], "Dark images": [[83, "Dark-images"]], "View top examples of dark images": [[83, "View-top-examples-of-dark-images"]], "Low information images": [[83, "Low-information-images"]], "The Workflows of Data-centric AI for Classification with Noisy Labels": [[84, "The-Workflows-of-Data-centric-AI-for-Classification-with-Noisy-Labels"]], "Create the data (can skip these details)": [[84, "Create-the-data-(can-skip-these-details)"]], "Workflow 1: Use Datalab to detect many types of issues": [[84, "Workflow-1:-Use-Datalab-to-detect-many-types-of-issues"]], "Workflow 2: Use CleanLearning for more robust Machine Learning": [[84, "Workflow-2:-Use-CleanLearning-for-more-robust-Machine-Learning"]], "Clean Learning = Machine Learning with cleaned data": [[84, "Clean-Learning-=-Machine-Learning-with-cleaned-data"]], "Workflow 3: Use CleanLearning to find_label_issues in one line of code": [[84, "Workflow-3:-Use-CleanLearning-to-find_label_issues-in-one-line-of-code"]], "Visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[84, "Visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 4: Use cleanlab to find dataset-level and class-level issues": [[84, "Workflow-4:-Use-cleanlab-to-find-dataset-level-and-class-level-issues"]], "Now, let\u2019s see what happens if we merge classes \u201cseafoam green\u201d and \u201cyellow\u201d": [[84, "Now,-let's-see-what-happens-if-we-merge-classes-%22seafoam-green%22-and-%22yellow%22"]], "Workflow 5: Clean your test set too if you\u2019re doing ML with noisy labels!": [[84, "Workflow-5:-Clean-your-test-set-too-if-you're-doing-ML-with-noisy-labels!"]], "Workflow 6: One score to rule them all \u2013 use cleanlab\u2019s overall dataset health score": [[84, "Workflow-6:-One-score-to-rule-them-all----use-cleanlab's-overall-dataset-health-score"]], "How accurate is this dataset health score?": [[84, "How-accurate-is-this-dataset-health-score?"]], "Workflow(s) 7: Use count, rank, filter modules directly": [[84, "Workflow(s)-7:-Use-count,-rank,-filter-modules-directly"]], "Workflow 7.1 (count): Fully characterize label noise (noise matrix, joint, prior of true labels, \u2026)": [[84, "Workflow-7.1-(count):-Fully-characterize-label-noise-(noise-matrix,-joint,-prior-of-true-labels,-...)"]], "Use cleanlab to estimate and visualize the joint distribution of label noise and noise matrix of label flipping rates:": [[84, "Use-cleanlab-to-estimate-and-visualize-the-joint-distribution-of-label-noise-and-noise-matrix-of-label-flipping-rates:"]], "Workflow 7.2 (filter): Find label issues for any dataset and any model in one line of code": [[84, "Workflow-7.2-(filter):-Find-label-issues-for-any-dataset-and-any-model-in-one-line-of-code"]], "Again, we can visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[84, "Again,-we-can-visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 7.2 supports lots of methods to find_label_issues() via the filter_by parameter.": [[84, "Workflow-7.2-supports-lots-of-methods-to-find_label_issues()-via-the-filter_by-parameter."]], "Workflow 7.3 (rank): Automatically rank every example by a unique label quality score. Find errors using cleanlab.count.num_label_issues as a threshold.": [[84, "Workflow-7.3-(rank):-Automatically-rank-every-example-by-a-unique-label-quality-score.-Find-errors-using-cleanlab.count.num_label_issues-as-a-threshold."]], "Again, we can visualize the label issues found to see if Cleanlab works.": [[84, "Again,-we-can-visualize-the-label-issues-found-to-see-if-Cleanlab-works."]], "Not sure when to use Workflow 7.2 or 7.3 to find label issues?": [[84, "Not-sure-when-to-use-Workflow-7.2-or-7.3-to-find-label-issues?"]], "Workflow 8: Ensembling label quality scores from multiple predictors": [[84, "Workflow-8:-Ensembling-label-quality-scores-from-multiple-predictors"]], "Tutorials": [[85, "tutorials"]], "Estimate Consensus and Annotator Quality for Data Labeled by Multiple Annotators": [[86, "Estimate-Consensus-and-Annotator-Quality-for-Data-Labeled-by-Multiple-Annotators"]], "2. Create the data (can skip these details)": [[86, "2.-Create-the-data-(can-skip-these-details)"]], "3. Get initial consensus labels via majority vote and compute out-of-sample predicted probabilities": [[86, "3.-Get-initial-consensus-labels-via-majority-vote-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to get better consensus labels and other statistics": [[86, "4.-Use-cleanlab-to-get-better-consensus-labels-and-other-statistics"]], "Comparing improved consensus labels": [[86, "Comparing-improved-consensus-labels"]], "Inspecting consensus quality scores to find potential consensus label errors": [[86, "Inspecting-consensus-quality-scores-to-find-potential-consensus-label-errors"]], "5. Retrain model using improved consensus labels": [[86, "5.-Retrain-model-using-improved-consensus-labels"]], "Further improvements": [[86, "Further-improvements"]], "How does cleanlab.multiannotator work?": [[86, "How-does-cleanlab.multiannotator-work?"]], "Find Label Errors in Multi-Label Classification Datasets": [[87, "Find-Label-Errors-in-Multi-Label-Classification-Datasets"]], "1. Install required dependencies and get dataset": [[87, "1.-Install-required-dependencies-and-get-dataset"]], "2. Format data, labels, and model predictions": [[87, "2.-Format-data,-labels,-and-model-predictions"], [88, "2.-Format-data,-labels,-and-model-predictions"]], "3. Use cleanlab to find label issues": [[87, "3.-Use-cleanlab-to-find-label-issues"], [88, "3.-Use-cleanlab-to-find-label-issues"], [92, "3.-Use-cleanlab-to-find-label-issues"], [95, "3.-Use-cleanlab-to-find-label-issues"]], "Label quality scores": [[87, "Label-quality-scores"]], "Data issues beyond mislabeling (outliers, duplicates, drift, \u2026)": [[87, "Data-issues-beyond-mislabeling-(outliers,-duplicates,-drift,-...)"]], "How to format labels given as a one-hot (multi-hot) binary matrix?": [[87, "How-to-format-labels-given-as-a-one-hot-(multi-hot)-binary-matrix?"]], "Estimate label issues without Datalab": [[87, "Estimate-label-issues-without-Datalab"]], "Application to Real Data": [[87, "Application-to-Real-Data"]], "Finding Label Errors in Object Detection Datasets": [[88, "Finding-Label-Errors-in-Object-Detection-Datasets"]], "1. Install required dependencies and download data": [[88, "1.-Install-required-dependencies-and-download-data"], [92, "1.-Install-required-dependencies-and-download-data"], [95, "1.-Install-required-dependencies-and-download-data"]], "Get label quality scores": [[88, "Get-label-quality-scores"], [92, "Get-label-quality-scores"]], "4. Use ObjectLab to visualize label issues": [[88, "4.-Use-ObjectLab-to-visualize-label-issues"]], "Different kinds of label issues identified by ObjectLab": [[88, "Different-kinds-of-label-issues-identified-by-ObjectLab"]], "Other uses of visualize": [[88, "Other-uses-of-visualize"]], "Exploratory data analysis": [[88, "Exploratory-data-analysis"]], "Detect Outliers with Cleanlab and PyTorch Image Models (timm)": [[89, "Detect-Outliers-with-Cleanlab-and-PyTorch-Image-Models-(timm)"]], "1. Install the required dependencies": [[89, "1.-Install-the-required-dependencies"]], "2. Pre-process the Cifar10 dataset": [[89, "2.-Pre-process-the-Cifar10-dataset"]], "Visualize some of the training and test examples": [[89, "Visualize-some-of-the-training-and-test-examples"]], "3. Use cleanlab and feature embeddings to find outliers in the data": [[89, "3.-Use-cleanlab-and-feature-embeddings-to-find-outliers-in-the-data"]], "4. Use cleanlab and pred_probs to find outliers in the data": [[89, "4.-Use-cleanlab-and-pred_probs-to-find-outliers-in-the-data"]], "Computing Out-of-Sample Predicted Probabilities with Cross-Validation": [[90, "computing-out-of-sample-predicted-probabilities-with-cross-validation"]], "Out-of-sample predicted probabilities?": [[90, "out-of-sample-predicted-probabilities"]], "What is K-fold cross-validation?": [[90, "what-is-k-fold-cross-validation"]], "Find Noisy Labels in Regression Datasets": [[91, "Find-Noisy-Labels-in-Regression-Datasets"]], "3. Define a regression model and use cleanlab to find potential label errors": [[91, "3.-Define-a-regression-model-and-use-cleanlab-to-find-potential-label-errors"]], "4. Train a more robust model from noisy labels": [[91, "4.-Train-a-more-robust-model-from-noisy-labels"], [94, "4.-Train-a-more-robust-model-from-noisy-labels"]], "5. Other ways to find noisy labels in regression datasets": [[91, "5.-Other-ways-to-find-noisy-labels-in-regression-datasets"]], "Find Label Errors in Semantic Segmentation Datasets": [[92, "Find-Label-Errors-in-Semantic-Segmentation-Datasets"]], "2. Get data, labels, and pred_probs": [[92, "2.-Get-data,-labels,-and-pred_probs"], [95, "2.-Get-data,-labels,-and-pred_probs"]], "Visualize top label issues": [[92, "Visualize-top-label-issues"]], "Classes which are commonly mislabeled overall": [[92, "Classes-which-are-commonly-mislabeled-overall"]], "Focusing on one specific class": [[92, "Focusing-on-one-specific-class"]], "Classification with Tabular Data using Scikit-Learn and Cleanlab": [[93, "Classification-with-Tabular-Data-using-Scikit-Learn-and-Cleanlab"]], "4. Use cleanlab to find label issues": [[93, "4.-Use-cleanlab-to-find-label-issues"]], "5. Train a more robust model from noisy labels": [[93, "5.-Train-a-more-robust-model-from-noisy-labels"]], "Text Classification with Noisy Labels": [[94, "Text-Classification-with-Noisy-Labels"]], "3. Define a classification model and use cleanlab to find potential label errors": [[94, "3.-Define-a-classification-model-and-use-cleanlab-to-find-potential-label-errors"]], "Find Label Errors in Token Classification (Text) Datasets": [[95, "Find-Label-Errors-in-Token-Classification-(Text)-Datasets"]], "Most common word-level token mislabels": [[95, "Most-common-word-level-token-mislabels"]], "Find sentences containing a particular mislabeled word": [[95, "Find-sentences-containing-a-particular-mislabeled-word"]], "Sentence label quality score": [[95, "Sentence-label-quality-score"]], "How does cleanlab.token_classification work?": [[95, "How-does-cleanlab.token_classification-work?"]]}, "indexentries": {"cleanlab.benchmarking": [[0, "module-cleanlab.benchmarking"]], "module": [[0, "module-cleanlab.benchmarking"], [1, "module-cleanlab.benchmarking.noise_generation"], [2, "module-cleanlab.classification"], [3, "module-cleanlab.count"], [4, "module-cleanlab.datalab.datalab"], [9, 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(cleanlab.datalab.internal.data.multilabel property)": [[10, "cleanlab.datalab.internal.data.MultiLabel.class_names"]], "cleanlab.datalab.internal.data": [[10, "module-cleanlab.datalab.internal.data"]], "has_labels (cleanlab.datalab.internal.data.data property)": [[10, "cleanlab.datalab.internal.data.Data.has_labels"]], "is_available (cleanlab.datalab.internal.data.label property)": [[10, "cleanlab.datalab.internal.data.Label.is_available"]], "is_available (cleanlab.datalab.internal.data.multiclass property)": [[10, "cleanlab.datalab.internal.data.MultiClass.is_available"]], "is_available (cleanlab.datalab.internal.data.multilabel property)": [[10, "cleanlab.datalab.internal.data.MultiLabel.is_available"]], "with_traceback() (cleanlab.datalab.internal.data.dataformaterror method)": [[10, "cleanlab.datalab.internal.data.DataFormatError.with_traceback"]], "with_traceback() (cleanlab.datalab.internal.data.datasetdicterror method)": [[10, 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"set_health_score() (cleanlab.datalab.internal.data_issues.dataissues method)": [[11, "cleanlab.datalab.internal.data_issues.DataIssues.set_health_score"]], "statistics (cleanlab.datalab.internal.data_issues.dataissues property)": [[11, "cleanlab.datalab.internal.data_issues.DataIssues.statistics"]], "registry (in module cleanlab.datalab.internal.issue_manager_factory)": [[12, "cleanlab.datalab.internal.issue_manager_factory.REGISTRY"]], "cleanlab.datalab.internal.issue_manager_factory": [[12, "module-cleanlab.datalab.internal.issue_manager_factory"]], "list_default_issue_types() (in module cleanlab.datalab.internal.issue_manager_factory)": [[12, "cleanlab.datalab.internal.issue_manager_factory.list_default_issue_types"]], "list_possible_issue_types() (in module cleanlab.datalab.internal.issue_manager_factory)": [[12, "cleanlab.datalab.internal.issue_manager_factory.list_possible_issue_types"]], "register() (in module cleanlab.datalab.internal.issue_manager_factory)": [[12, "cleanlab.datalab.internal.issue_manager_factory.register"]], "cleanlab.datalab.internal": [[13, "module-cleanlab.datalab.internal"]], "issuefinder (class in cleanlab.datalab.internal.issue_finder)": [[14, "cleanlab.datalab.internal.issue_finder.IssueFinder"]], "cleanlab.datalab.internal.issue_finder": [[14, "module-cleanlab.datalab.internal.issue_finder"]], "find_issues() (cleanlab.datalab.internal.issue_finder.issuefinder method)": [[14, "cleanlab.datalab.internal.issue_finder.IssueFinder.find_issues"]], "get_available_issue_types() (cleanlab.datalab.internal.issue_finder.issuefinder method)": [[14, "cleanlab.datalab.internal.issue_finder.IssueFinder.get_available_issue_types"]], "default_threshold (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.DEFAULT_THRESHOLD"]], "datavaluationissuemanager (class in cleanlab.datalab.internal.issue_manager.data_valuation)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager"]], "cleanlab.datalab.internal.issue_manager.data_valuation": [[16, "module-cleanlab.datalab.internal.issue_manager.data_valuation"]], "collect_info() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager method)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager method)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.find_issues"]], "info 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"cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager class method)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[16, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.verbosity_levels"]], "nearduplicateissuemanager (class in cleanlab.datalab.internal.issue_manager.duplicate)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager"]], "cleanlab.datalab.internal.issue_manager.duplicate": [[17, "module-cleanlab.datalab.internal.issue_manager.duplicate"]], "collect_info() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager method)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager method)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager class method)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.make_summary"]], "near_duplicate_sets (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[17, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.near_duplicate_sets"]], "report() 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"get_normalized_margin_for_each_label() (in module cleanlab.rank)": [[61, "cleanlab.rank.get_normalized_margin_for_each_label"]], "get_self_confidence_for_each_label() (in module cleanlab.rank)": [[61, "cleanlab.rank.get_self_confidence_for_each_label"]], "order_label_issues() (in module cleanlab.rank)": [[61, "cleanlab.rank.order_label_issues"]], "cleanlab.regression": [[62, "module-cleanlab.regression"]], "cleanlearning (class in cleanlab.regression.learn)": [[63, "cleanlab.regression.learn.CleanLearning"]], "__init_subclass__() (cleanlab.regression.learn.cleanlearning class method)": [[63, "cleanlab.regression.learn.CleanLearning.__init_subclass__"]], "cleanlab.regression.learn": [[63, "module-cleanlab.regression.learn"]], "find_label_issues() (cleanlab.regression.learn.cleanlearning method)": [[63, "cleanlab.regression.learn.CleanLearning.find_label_issues"]], "fit() (cleanlab.regression.learn.cleanlearning method)": [[63, "cleanlab.regression.learn.CleanLearning.fit"]], 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diff --git a/master/tutorials/audio.ipynb b/master/tutorials/audio.ipynb
index 689113d37..2694b2d34 100644
--- a/master/tutorials/audio.ipynb
+++ b/master/tutorials/audio.ipynb
@@ -78,10 +78,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:31:37.224478Z",
-     "iopub.status.busy": "2024-02-13T00:31:37.224129Z",
-     "iopub.status.idle": "2024-02-13T00:31:41.940534Z",
-     "shell.execute_reply": "2024-02-13T00:31:41.939994Z"
+     "iopub.execute_input": "2024-02-13T00:56:39.860413Z",
+     "iopub.status.busy": "2024-02-13T00:56:39.860233Z",
+     "iopub.status.idle": "2024-02-13T00:56:44.841725Z",
+     "shell.execute_reply": "2024-02-13T00:56:44.841150Z"
     },
     "nbsphinx": "hidden"
    },
@@ -97,7 +97,7 @@
     "os.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\" \n",
     "\n",
     "if \"google.colab\" in str(get_ipython()):  # Check if it's running in Google Colab\n",
-    "    %pip install git+https://github.com/cleanlab/cleanlab.git@5408abe9bf41d8c765c17e338a0745474e55460a\n",
+    "    %pip install git+https://github.com/cleanlab/cleanlab.git@1ed51aa35af86c70d2f0f30ffc087f4972a8cdf8\n",
     "    cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
     "    %pip install $cmd\n",
     "else:\n",
@@ -131,10 +131,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:31:41.943221Z",
-     "iopub.status.busy": "2024-02-13T00:31:41.942735Z",
-     "iopub.status.idle": "2024-02-13T00:31:41.946336Z",
-     "shell.execute_reply": "2024-02-13T00:31:41.945907Z"
+     "iopub.execute_input": "2024-02-13T00:56:44.844367Z",
+     "iopub.status.busy": "2024-02-13T00:56:44.843991Z",
+     "iopub.status.idle": "2024-02-13T00:56:44.847404Z",
+     "shell.execute_reply": "2024-02-13T00:56:44.846906Z"
     },
     "id": "LaEiwXUiVHCS"
    },
@@ -157,10 +157,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:31:41.948296Z",
-     "iopub.status.busy": "2024-02-13T00:31:41.947971Z",
-     "iopub.status.idle": "2024-02-13T00:31:41.952648Z",
-     "shell.execute_reply": "2024-02-13T00:31:41.952243Z"
+     "iopub.execute_input": "2024-02-13T00:56:44.849416Z",
+     "iopub.status.busy": "2024-02-13T00:56:44.849066Z",
+     "iopub.status.idle": "2024-02-13T00:56:44.853654Z",
+     "shell.execute_reply": "2024-02-13T00:56:44.853228Z"
     },
     "nbsphinx": "hidden"
    },
@@ -208,10 +208,10 @@
      "base_uri": "https://localhost:8080/"
     },
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:31:41.954653Z",
-     "iopub.status.busy": "2024-02-13T00:31:41.954323Z",
-     "iopub.status.idle": "2024-02-13T00:31:42.732996Z",
-     "shell.execute_reply": "2024-02-13T00:31:42.732216Z"
+     "iopub.execute_input": "2024-02-13T00:56:44.855852Z",
+     "iopub.status.busy": "2024-02-13T00:56:44.855448Z",
+     "iopub.status.idle": "2024-02-13T00:56:46.523185Z",
+     "shell.execute_reply": "2024-02-13T00:56:46.522402Z"
     },
     "id": "GRDPEg7-VOQe",
     "outputId": "cb886220-e86e-4a77-9f3a-d7844c37c3a6"
@@ -242,10 +242,10 @@
      "base_uri": "https://localhost:8080/"
     },
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:31:42.735948Z",
-     "iopub.status.busy": "2024-02-13T00:31:42.735408Z",
-     "iopub.status.idle": "2024-02-13T00:31:42.745825Z",
-     "shell.execute_reply": "2024-02-13T00:31:42.745309Z"
+     "iopub.execute_input": "2024-02-13T00:56:46.526190Z",
+     "iopub.status.busy": "2024-02-13T00:56:46.525734Z",
+     "iopub.status.idle": "2024-02-13T00:56:46.536366Z",
+     "shell.execute_reply": "2024-02-13T00:56:46.535798Z"
     },
     "id": "FDA5sGZwUSur",
     "outputId": "0cedc509-63fd-4dc3-d32f-4b537dfe3895"
@@ -329,10 +329,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:31:42.776336Z",
-     "iopub.status.busy": "2024-02-13T00:31:42.775971Z",
-     "iopub.status.idle": "2024-02-13T00:31:42.781528Z",
-     "shell.execute_reply": "2024-02-13T00:31:42.780973Z"
+     "iopub.execute_input": "2024-02-13T00:56:46.567729Z",
+     "iopub.status.busy": "2024-02-13T00:56:46.567277Z",
+     "iopub.status.idle": "2024-02-13T00:56:46.573208Z",
+     "shell.execute_reply": "2024-02-13T00:56:46.572615Z"
     },
     "nbsphinx": "hidden"
    },
@@ -380,10 +380,10 @@
      "height": 92
     },
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:31:42.783618Z",
-     "iopub.status.busy": "2024-02-13T00:31:42.783324Z",
-     "iopub.status.idle": "2024-02-13T00:31:43.229412Z",
-     "shell.execute_reply": "2024-02-13T00:31:43.228845Z"
+     "iopub.execute_input": "2024-02-13T00:56:46.575280Z",
+     "iopub.status.busy": "2024-02-13T00:56:46.574957Z",
+     "iopub.status.idle": "2024-02-13T00:56:47.004687Z",
+     "shell.execute_reply": "2024-02-13T00:56:47.004191Z"
     },
     "id": "dLBvUZLlII5w",
     "outputId": "c6a4917f-4a82-4a89-9193-415072e45550"
@@ -435,10 +435,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:31:43.231493Z",
-     "iopub.status.busy": "2024-02-13T00:31:43.231303Z",
-     "iopub.status.idle": "2024-02-13T00:31:43.832329Z",
-     "shell.execute_reply": "2024-02-13T00:31:43.831716Z"
+     "iopub.execute_input": "2024-02-13T00:56:47.006892Z",
+     "iopub.status.busy": "2024-02-13T00:56:47.006531Z",
+     "iopub.status.idle": "2024-02-13T00:56:48.255788Z",
+     "shell.execute_reply": "2024-02-13T00:56:48.255169Z"
     },
     "id": "vL9lkiKsHvKr"
    },
@@ -474,10 +474,10 @@
      "height": 143
     },
     "execution": {
-     "iopub.execute_input": "2024-02-13T00:31:43.834985Z",
-     "iopub.status.busy": "2024-02-13T00:31:43.834608Z",
-     "iopub.status.idle": "2024-02-13T00:31:43.853277Z",
-     "shell.execute_reply": "2024-02-13T00:31:43.852836Z"
+     "iopub.execute_input": "2024-02-13T00:56:48.258090Z",
+     "iopub.status.busy": "2024-02-13T00:56:48.257904Z",
+     "iopub.status.idle": "2024-02-13T00:56:48.276092Z",
+     "shell.execute_reply": "2024-02-13T00:56:48.275602Z"
     },
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diff --git a/master/tutorials/datalab/datalab_advanced.html b/master/tutorials/datalab/datalab_advanced.html
index 0a6ac5535..d75e2fe1e 100644
--- a/master/tutorials/datalab/datalab_advanced.html
+++ b/master/tutorials/datalab/datalab_advanced.html
@@ -1209,7 +1209,7 @@ 
    Functionality 3: Save and load Datalab objects