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Functions3,759 in github.com/huggingface/sentence-transformers

⨍ Functions 3,759◇ Types & classes 446↳ Endpoints 48
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_sparse_encoder_distillation_example.py:95
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_sentence_transformer_with_lora_example.py:140
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_sentence_transformer_example.py:101
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_sentence_transformer_matryoshka_example.py:79
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_cross_encoder_distillation_example.py:98
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_multi_vector_encoder_example.py:102
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_sparse_encoder_example.py:90
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_cross_encoder_listwise_example.py:109
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_sentence_transformer_multi_dataset_example.py:124
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_sentence_transformer_static_embedding_example.py:116
↓ 1 callersFunctionsetup_logging
Configure logging + TF32. Tees to logs/{RUN_NAME}.log and silences HTTP spam.
skills/train-sentence-transformers/scripts/train_sentence_transformer_distillation_example.py:132
↓ 1 callersMethodshould_dataset_name_column_be_added
We should add a dataset name column to the dataset, if the dataset is a DatasetDict, *and* one of: a. The loss is a dictionary, or
sentence_transformers/base/trainer.py:1112
↓ 1 callersMethodsim_matrix
(self, embed1: Tensor, embed2: Tensor)
sentence_transformers/sentence_transformer/losses/cached_gist_embed.py:178
↓ 1 callersMethodsim_matrix
(self, embed1: Tensor, embed2: Tensor)
sentence_transformers/sentence_transformer/losses/gist_embed.py:137
↓ 1 callersMethodsimilarity_pairwise
Compute the similarity between two collections of embeddings. The output will be a vector with the similarity scores between each pai
sentence_transformers/sparse_encoder/model.py:900
↓ 1 callersFunctionstatic_embedding
(tokenizer: Tokenizer, embedding_weights)
tests/conftest.py:205
↓ 1 callersFunctionstationary_distribution
(transition_matrix, increase_power=True, normalized=True)
examples/sentence_transformer/applications/text-summarization/lex_rank.py:96
↓ 1 callersMethodstop
(self)
examples/sentence_transformer/evaluation/evaluation_no_dup_batch_sampler_speed.py:274
↓ 1 callersMethodstore_metrics_in_model_card_data
( self, model: SparseEncoder, metrics: dict[str, Any], epoch: int = 0, step: int = 0 )
sentence_transformers/sparse_encoder/evaluation/sparse_information_retrieval.py:274
↓ 1 callersMethodstore_metrics_in_model_card_data
( self, model: SparseEncoder, metrics: dict[str, Any], epoch: int = 0, step: int = 0 )
sentence_transformers/sparse_encoder/evaluation/sparse_binary_classification.py:181
↓ 1 callersMethodstore_metrics_in_model_card_data
( self, model: SparseEncoder, metrics: dict[str, Any], epoch: int = 0, step: int = 0 )
sentence_transformers/sparse_encoder/evaluation/sparse_reranking.py:194
↓ 1 callersMethodstore_metrics_in_model_card_data
( self, model: SparseEncoder, metrics: dict[str, Any], epoch: int = 0, step: int = 0 )
sentence_transformers/sparse_encoder/evaluation/sparse_translation.py:149
↓ 1 callersMethodstore_metrics_in_model_card_data
( self, model: SparseEncoder, metrics: dict[str, Any], epoch: int = 0, step: int = 0 )
sentence_transformers/sparse_encoder/evaluation/sparse_triplet.py:189
↓ 1 callersMethodstore_metrics_in_model_card_data
( self, model: SparseEncoder, metrics: dict[str, Any], epoch: int = 0, step: int = 0 )
sentence_transformers/sparse_encoder/evaluation/sparse_embedding_similarity.py:159
↓ 1 callersFunctiontest
(model: SentenceTransformer, expected_dim: int)
tests/sentence_transformer/test_model.py:631
↓ 1 callersFunctionto_scipy_coo
Converts a sparse PyTorch tensor to a SciPy COO sparse matrix. Args: x (torch.Tensor): A 2-dimensional sparse PyTorch tensor in COO
sentence_transformers/util/tensor.py:321
↓ 1 callersFunctiontoken_labels
Readable labels for token ids: byte-level pieces decoded back to text, and the markers that tokenizers use to encode word boundaries (a leading sp
examples/multi_vector_encoder/interpretability/text_similarity_map.py:32
↓ 1 callersFunctiontokenize
(texts: list[str], task: str)
tests/multi_vector_encoder/test_evaluators.py:379
↓ 1 callersMethodtokenize
.. deprecated:: `tokenize` is deprecated. Use `preprocess` instead. Tokenizes the input texts and returns a dictionary o
sentence_transformers/base/modules/input_module.py:111
↓ 1 callersFunctiontokenizer
()
tests/conftest.py:195
↓ 1 callersMethodtop_k
:param x: input data (shape: [batch, input_dim]) :return: tuple of (top-k latents (shape: [batch, hidden_dim]), auxiliary latents or
sentence_transformers/sparse_encoder/modules/sparse_auto_encoder.py:113
↓ 1 callersFunctiontrec_dataset
(validation_dataset_nb=500)
examples/sentence_transformer/training/other/training_batch_hard_trec.py:39
↓ 1 callersFunctiontriplets_from_labeled_dataset
(dataset)
examples/sentence_transformer/training/other/training_batch_hard_trec.py:58
↓ 1 callersFunctiontruncate_embeddings
(embeddings: np.ndarray, truncate_dim: int | None)
sentence_transformers/util/tensor.py:141
↓ 1 callersMethodtry_to_set_base_model
(self)
sentence_transformers/base/model_card.py:1363
↓ 1 callersFunctionupdate_tiny_model_mapping
Update the tiny model mapping using the Hugging Face Hub API
tests/base/modules/transformer/update_transformers_tiny_models.py:65
↓ 1 callersMethodvalidate_column_names
(self, dataset: Dataset, dataset_name: str | None = None)
sentence_transformers/base/trainer.py:704
↓ 1 callersFunctionwrite_mining_files
(name, ids, dups)
examples/sentence_transformer/training/quora_duplicate_questions/create_splits.py:466
↓ 1 callersFunctionwrite_qids
(name, ids_list)
examples/sentence_transformer/training/quora_duplicate_questions/create_splits.py:454
↓ 1 callersFunctionxtr_scores_pairwise
Pairwise XTR scoring: compute the XTR score for matched ``(query_i, document_i)`` pairs. Returns a float32 1D tensor of length ``batch_size``. XT
sentence_transformers/multi_vector_encoder/scoring/xtr.py:158
Method__call__
(self, features)
sentence_transformers/sentence_transformer/losses/adaptive_layer.py:36
Method__call__
(self, features: dict[str, Tensor])
sentence_transformers/sentence_transformer/losses/adaptive_layer.py:73
Method__call__
(self, features: dict[str, Tensor])
sentence_transformers/sentence_transformer/losses/matryoshka.py:50
Method__call__
(self, reps: list[list[Tensor]], *args, **kwargs)
sentence_transformers/sentence_transformer/losses/matryoshka.py:88
Method__call__
Compute the evaluation metrics for the given model. Args: model (SentenceTransformer): The model to evaluate.
sentence_transformers/sentence_transformer/evaluation/binary_classification.py:151
Method__call__
Evaluates the model on the dataset and returns the evaluation metrics. Args: model (SentenceTransformer): The SentenceTr
sentence_transformers/sentence_transformer/evaluation/reranking.py:139
Method__call__
( self, model: SentenceTransformer, output_path: str | None = None, epoch=-1, steps=-1 )
sentence_transformers/sentence_transformer/evaluation/mse.py:97
Method__call__
( self, model: SentenceTransformer, output_path: str | None = None, epoch: int
sentence_transformers/sentence_transformer/evaluation/information_retrieval.py:218
Method__call__
( self, model: SentenceTransformer, output_path: str | None = None, epoch: int = -1, steps: int = -1
sentence_transformers/sentence_transformer/evaluation/triplet.py:175
Method__call__
( self, model: SentenceTransformer, output_path: str | None = None, epoch: int = -1, steps: int = -1
sentence_transformers/sentence_transformer/evaluation/label_accuracy.py:49
Method__call__
( self, model: SentenceTransformer, output_path: str | None = None, epoch: int = -1, steps: int = -1
sentence_transformers/sentence_transformer/evaluation/paraphrase_mining.py:156
Method__call__
( self, model: SentenceTransformer, output_path: str | None = None, epoch: int = -1, steps: int = -1
sentence_transformers/sentence_transformer/evaluation/translation.py:102
Method__call__
( self, model: SentenceTransformer, output_path: str | None = None, epoch: int = -1, steps: int = -1
sentence_transformers/sentence_transformer/evaluation/embedding_similarity.py:153
Method__call__
( self, model: SentenceTransformer, output_path: str | None = None, epoch: int = -1, steps: int = -1
sentence_transformers/sentence_transformer/evaluation/mse_from_dataframe.py:87
Method__call__
( self, model: SentenceTransformer, output_path: str | None = None, epoch: int
sentence_transformers/sentence_transformer/evaluation/nano_beir.py:306
Method__call__
( self, model: MultiVectorEncoder, output_path: str | None = None, epoch: int
sentence_transformers/multi_vector_encoder/evaluation/distillation.py:171
Method__call__
(self, model: MultiVectorEncoder, *args, **kwargs)
sentence_transformers/multi_vector_encoder/evaluation/reranking.py:88
Method__call__
( self, model: MultiVectorEncoder, output_path: str | None = None, epoch: int
sentence_transformers/multi_vector_encoder/evaluation/information_retrieval.py:155
Method__call__
( self, model: MultiVectorEncoder, output_path: str | None = None, epoch: int
sentence_transformers/multi_vector_encoder/evaluation/nano_beir.py:107
Method__call__
( self, queries_embeddings: list | np.ndarray | torch.Tensor, documents_embeddings: li
sentence_transformers/multi_vector_encoder/scoring/xtr.py:208
Method__call__
( self, queries_embeddings: list | np.ndarray | torch.Tensor, documents_embeddings: li
sentence_transformers/multi_vector_encoder/scoring/xtr.py:228
Method__call__
(self, features: list[dict[str, Any]])
sentence_transformers/cross_encoder/data_collator.py:47
Method__call__
( self, model: CrossEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1 )
sentence_transformers/cross_encoder/evaluation/classification.py:102
Method__call__
( self, model: CrossEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1 )
sentence_transformers/cross_encoder/evaluation/reranking.py:139
Method__call__
( self, model: CrossEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1 )
sentence_transformers/cross_encoder/evaluation/correlation.py:100
Method__call__
( self, model: CrossEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1, *args,
sentence_transformers/cross_encoder/evaluation/nano_beir.py:250
Method__call__
( self, model: SparseEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1, *args,
sentence_transformers/sparse_encoder/evaluation/sparse_information_retrieval.py:202
Method__call__
( self, model: SparseEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1 )
sentence_transformers/sparse_encoder/evaluation/sparse_binary_classification.py:140
Method__call__
( self, model: SparseEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1 )
sentence_transformers/sparse_encoder/evaluation/sparse_reranking.py:140
Method__call__
( self, model: SparseEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1 )
sentence_transformers/sparse_encoder/evaluation/sparse_translation.py:107
Method__call__
( self, model: SparseEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1 )
sentence_transformers/sparse_encoder/evaluation/sparse_triplet.py:134
Method__call__
(self, output_path: str | None = None, epoch: int = -1, steps: int = -1)
sentence_transformers/sparse_encoder/evaluation/reciprocal_rank_fusion.py:105
Method__call__
( self, model: SparseEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1 )
sentence_transformers/sparse_encoder/evaluation/sparse_embedding_similarity.py:118
Method__call__
( self, model: SparseEncoder, output_path: str | None = None, epoch: int = -1,
sentence_transformers/sparse_encoder/evaluation/sparse_mse.py:112
Method__call__
( self, model: SparseEncoder, output_path: str | None = None, epoch: int = -1, steps: int = -1, *args,
sentence_transformers/sparse_encoder/evaluation/sparse_nano_beir.py:266
Method__call__
(self, features: list[dict[str, Any]])
sentence_transformers/base/data_collator.py:97
Method__call__
This is called during training to evaluate the model. It returns a score for the evaluation with a higher score indicating a better r
sentence_transformers/base/evaluation/evaluator.py:27
Method__call__
( self, model: BaseModel, output_path: str | None = None, epoch: int = -1, steps: int = -1 )
sentence_transformers/base/evaluation/sequential.py:38
Method__call__
(self, sentence_feature: dict[str, torch.Tensor])
tests/sentence_transformer/losses/test_contrastive.py:16
Method__call__
(self, features: dict[str, Tensor], task: str | None = None)
tests/multi_vector_encoder/losses/test_misc.py:35
Method__call__
(self, features: dict[str, Tensor], task: str | None = None)
tests/multi_vector_encoder/losses/test_misc.py:84
Method__call__
(self, features: dict[str, Tensor], task: str | None = None)
tests/multi_vector_encoder/losses/test_misc.py:216
Method__call__
(self, features: dict[str, Tensor], task: str | None = None)
tests/multi_vector_encoder/losses/test_misc.py:314
Method__call__
(self, features: dict[str, Tensor], task: str | None = None)
tests/multi_vector_encoder/losses/test_misc.py:351
Method__call__
(self, features: dict[str, Tensor], task: str | None = None)
tests/multi_vector_encoder/losses/test_misc.py:582
Method__call__
(self, *args, **kwargs)
tests/sparse_encoder/modules/test_csr.py:19
Method__call__
(self, model, output_path=None, epoch=-1, steps=-1)
tests/base/test_model.py:543
Method__call__
(self, a, b)
tests/util/test_misc.py:215
Method__contains__
(self, key)
tests/base/modules/test_transformer.py:622
Method__delattr__
Fix for https://github.com/huggingface/huggingface_hub/issues/1603
sentence_transformers/util/file_io.py:25
Method__enter__
(self)
sentence_transformers/base/losses/gradcache.py:47
Method__exit__
(self, exc_type, exc_val, exc_tb)
sentence_transformers/base/losses/gradcache.py:58
Method__getattr__
Provide backward compatibility for renamed methods. We use ``__getattr__`` instead of defining regular deprecated methods so that ``h
sentence_transformers/base/modules/module.py:457
Method__getattr__
(self, name)
tests/sentence_transformer/evaluation/test_information_retrieval_evaluator.py:39
Method__getitem__
(self, item)
sentence_transformers/sentence_transformer/datasets/denoising_auto_encoder.py:40
Method__getitem__
(self, idx)
sentence_transformers/sentence_transformer/datasets/parallel_sentences.py:203
Method__getitem__
(self, item)
sentence_transformers/sentence_transformer/datasets/sentences.py:30
Method__getitem__
(self, idx: int)
tests/base/test_model_card.py:1032
Method__getitem__
(self, key)
tests/base/modules/test_transformer.py:619
Method__getitem__
(self, key)
tests/base/modules/test_transformer.py:641
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