Merge branch 'master' into pr-2712

.github/workflows/quality.yml

@@ -20,7 +20,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
-        uses: actions/checkout@v2
+        uses: actions/checkout@v4
       - name: Setup Python environment
         uses: actions/setup-python@v5
         with:

.github/workflows/tests.yml

@@ -22,16 +22,37 @@ jobs:
       fail-fast: false
     runs-on: ${{ matrix.os }}
     steps:
+      - name: Remove unnecessary files
+        run: |
+          df -h /
+          # Remove software and language runtimes we're not using
+          sudo rm -rf \
+            "$AGENT_TOOLSDIRECTORY" \
+            /opt/google/chrome \
+            /opt/microsoft/msedge \
+            /opt/microsoft/powershell \
+            /opt/pipx \
+            /usr/lib/mono \
+            /usr/local/julia* \
+            /usr/local/lib/android \
+            /usr/local/lib/node_modules \
+            /usr/local/share/chromium \
+            /usr/local/share/powershell \
+            /usr/share/dotnet \
+            /usr/share/swift
+          df -h /
+        if: runner.os == 'Linux'
+
       - name: Checkout code
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
 
       - name: Setup Python environment
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
 
       - name: Try to load cached dependencies
-        uses: actions/cache@v3
+        uses: actions/cache@v4
         id: restore-cache
         with:
           path: ${{ env.pythonLocation }}

docs/conf.py

@@ -67,6 +67,7 @@
 intersphinx_mapping = {
     "datasets": ("https://huggingface.co/docs/datasets/main/en/", None),
     "transformers": ("https://huggingface.co/docs/transformers/main/en/", None),
+    "huggingface_hub": ("https://huggingface.co/docs/huggingface_hub/main/en/", None),
     "torch": ("https://pytorch.org/docs/stable/", None),
 }
 

docs/cross_encoder/usage/usage.rst

@@ -9,7 +9,7 @@ Characteristics of Cross Encoder (a.k.a reranker) models:
 3. Often **slower** than a Sentence Transformer model, as it requires computation for each pair rather than each text.
 4. Due to the previous 2 characteristics, Cross Encoders are often used to **re-rank the top-k results** from a Sentence Transformer model.
 
-Once you have installed `installed <installation.md>`_ Sentence Transformers, you can easily use Cross Encoder models:
+Once you have `installed <../../installation.html>`_ Sentence Transformers, you can easily use Cross Encoder models:
 
 .. sidebar:: Documentation
 

docs/package_reference/sentence_transformer/index.rst

@@ -8,6 +8,7 @@ Sentence Transformer
    trainer
    training_args
    losses
+   sampler
    evaluation
    datasets
    models

docs/package_reference/sentence_transformer/losses.md

@@ -135,6 +135,12 @@ This allows our network to be fine-tuned to recognize the similarity of sentence
 .. autoclass:: sentence_transformers.losses.MultipleNegativesSymmetricRankingLoss
 ```
 
+## CachedMultipleNegativesSymmetricRankingLoss
+
+```eval_rst
+.. autoclass:: sentence_transformers.losses.CachedMultipleNegativesSymmetricRankingLoss
+```
+
 ## SoftmaxLoss
 ```eval_rst
 .. autoclass:: sentence_transformers.losses.SoftmaxLoss

docs/package_reference/sentence_transformer/sampler.md

@@ -0,0 +1,39 @@
+
+# Samplers
+
+## BatchSamplers
+```eval_rst
+.. autoclass:: sentence_transformers.training_args.BatchSamplers
+    :members:
+```
+
+```eval_rst
+.. autoclass:: sentence_transformers.sampler.DefaultBatchSampler
+    :members:
+```
+
+```eval_rst
+.. autoclass:: sentence_transformers.sampler.NoDuplicatesBatchSampler
+    :members:
+```
+
+```eval_rst
+.. autoclass:: sentence_transformers.sampler.GroupByLabelBatchSampler
+    :members:
+```
+
+## MultiDatasetBatchSamplers
+```eval_rst
+.. autoclass:: sentence_transformers.training_args.MultiDatasetBatchSamplers
+    :members:
+```
+
+```eval_rst
+.. autoclass:: sentence_transformers.sampler.RoundRobinBatchSampler
+    :members:
+```
+
+```eval_rst
+.. autoclass:: sentence_transformers.sampler.ProportionalBatchSampler
+    :members:
+```

docs/package_reference/sentence_transformer/training_args.md

@@ -7,15 +7,3 @@
     :members:
     :inherited-members:
 ```
-
-## BatchSamplers
-```eval_rst
-.. autoclass:: sentence_transformers.training_args.BatchSamplers
-    :members:
-```
-
-## MultiDatasetBatchSamplers
-```eval_rst
-.. autoclass:: sentence_transformers.training_args.MultiDatasetBatchSamplers
-    :members:
-```

docs/quickstart.rst

@@ -11,7 +11,7 @@ Characteristics of Sentence Transformer (a.k.a bi-encoder) models:
 3. Applicable for a **wide range of tasks**, such as semantic textual similarity, semantic search, clustering, classification, paraphrase mining, and more.
 4. Often used as a **first step in a two-step retrieval process**, where a Cross-Encoder (a.k.a. reranker) model is used to re-rank the top-k results from the bi-encoder.
 
-Once you have `installed <installation.md>`_ Sentence Transformers, you can easily use Sentence Transformer models:
+Once you have `installed <installation.html>`_ Sentence Transformers, you can easily use Sentence Transformer models:
 
 .. sidebar:: Documentation