huggingface/sentence-transformers
State-of-the-Art Embeddings, Retrieval, and Reranking
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Apache-2.0
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Documents
- Evaluationsentence_transformers.multi_vector_encoder.evaluation defines evaluators tailored to multi-vector (late-interaction) models. All evaluators score with MaxSim and accept the multi-vector model's ragge…docs/package_reference/multi_vector_encoder/evaluation.md
- index.rstdocs/package_reference/multi_vector_encoder/index.rst
- Interpretabilitysentence_transformers.multi_vector_encoder.interpretability provides a per-query-token MaxSim heatmap utility for ColPali-style image documents. Useful for spot-checking which patch positions in an i…docs/package_reference/multi_vector_encoder/interpretability.md
- Lossessentence_transformers.multi_vector_encoder.losses defines the loss functions for training MultiVectorEncoder models. See Training Overview for guidance on which loss to pick for which dataset format.docs/package_reference/multi_vector_encoder/losses.md
- MultiVectorEncoderdocs/package_reference/multi_vector_encoder/model.md
- Modulessentence_transformers.multi_vector_encoder.modules defines the building blocks specific to multi-vector models. Combined with the shared backbone in sentence_transformers.base.modules (see Base > Mod…docs/package_reference/multi_vector_encoder/modules.md
- Scoringsentence_transformers.multi_vector_encoder.scoring provides the late-interaction scoring functions used by training losses. Pass one of these (or a configured callable) as the similarity_fct paramete…docs/package_reference/multi_vector_encoder/scoring.md
- Trainerdocs/package_reference/multi_vector_encoder/trainer.md
- Training Argumentsdocs/package_reference/multi_vector_encoder/training_args.md