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Modules

docs/package_reference/multi_vector_encoder/modules.md

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Modules

sentence_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 > Modules), they make up the standard ColBERT-style stack: Transformer -> Dense -> MultiVectorMask -> Normalize.

See also Training Overview.

MultiVectorMask

{eval-rst}
.. autoclass:: sentence_transformers.multi_vector_encoder.modules.MultiVectorMask

BaseTokenPooling

{eval-rst}
.. autoclass:: sentence_transformers.multi_vector_encoder.modules.BaseTokenPooling
    :members: pool, forward

HierarchicalTokenPooling

{eval-rst}
.. autoclass:: sentence_transformers.multi_vector_encoder.modules.HierarchicalTokenPooling

LambdaTokenPooling

{eval-rst}
.. autoclass:: sentence_transformers.multi_vector_encoder.modules.LambdaTokenPooling