colbert-bert-tiny

This is a ColBERT model finetuned from google/bert_uncased_L-2_H-128_A-2 on the msmarco-bm25 dataset. It maps sentences & paragraphs to sequences of 128-dimensional dense vectors and can be used for semantic textual similarity using the MaxSim operator. This model is primarily designed for unit tests in limited compute environments such as GitHub Actions. But it does work to an extent for basic use cases. As of Sentence Transformers v6.0.0, this model loads directly as a multi-vector (ColBERT-style late interaction) retriever via the `MultiVectorEncoder`:

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