better format for div code blocks, add missing dependencies to requir…

…ements.txt(#28)

multilabel_classification/image_tagging.ipynb

@@ -15,28 +15,20 @@
    "id": "adaefc8b-b639-4bdf-af0d-337519e37ffc",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-info\">\n",
-    "Quickstart\n",
-    "<br/>\n",
-    "    \n",
-    "cleanlab finds label issues based on two inputs: `labels` formatted as a list of lists of integer class indices that apply to each example in your dataset, and `pred_probs` from a trained multi-label classification model (which do not need to sum to 1 since the classes are not mutually exclusive). Once you have these, run the code below to find label issues in your dataset.\n",
-    "\n",
-    "<div  class=markdown markdown=\"1\" style=\"background:white;margin:16px\">  \n",
-    "    \n",
-    "```ipython3 \n",
-    "from cleanlab.filter import find_label_issues\n",
-    "\n",
-    "ranked_label_issues = find_label_issues(\n",
-    "    labels=labels,\n",
-    "    pred_probs=pred_probs,\n",
-    "    multi_label=True,\n",
-    "    return_indices_ranked_by=\"self_confidence\",\n",
-    ")\n",
-    "```\n",
-    "\n",
-    "    \n",
-    "</div>\n",
-    "</div>"
+    "> ## Quickstart\n",
+    ">     \n",
+    "> cleanlab finds label issues based on two inputs: `labels` formatted as a list of lists of integer class indices that apply to each example in your dataset, and `pred_probs` from a trained multi-label classification model (which do not need to sum to 1 since the classes are not mutually exclusive). Once you have these, run the code below to find label issues in your dataset.\n",
+    ">     \n",
+    "> ```ipython3 \n",
+    "> from cleanlab.filter import find_label_issues\n",
+    "> \n",
+    "> ranked_label_issues = find_label_issues(\n",
+    ">     labels=labels,\n",
+    ">     pred_probs=pred_probs,\n",
+    ">     multi_label=True,\n",
+    ">     return_indices_ranked_by=\"self_confidence\",\n",
+    "> )\n",
+    "> ```"
    ]
   },
   {

requirements.txt

@@ -1,6 +1,7 @@
 cleanlab # Some examples may require you to instead install latest developer version of cleanlab from github: pip install git+https://github.com/cleanlab/cleanlab.git
 annoy==1.17.1
 autogluon.vision==0.5.2
+gdown==4.5.3
 ipykernel==6.15.2
 ipywidgets==8.0.2
 jupyterlab
@@ -18,6 +19,8 @@ six==1.16.0
 statsmodels==0.13.2
 tensorflow==2.9.2 # for Macs with Apple silicon : tensorflow-macos==2.9.2 and tensorflow-metal==0.5.1
 tensorflow-datasets==4.6.0
+timm
+torch==1.12.1
 tqdm>=4.64.0
 transformers==4.22.0.dev0
 black[jupyter]