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ColBERTgithub.comColBERT is a fast, accurate retrieval model that enables scalable BERT-based search over large text collections in tens of milliseconds. It uses fine-grained contextual late interaction, encoding passages into token-level embeddings and computing query embeddings to efficiently score passages via scalable vector similarity (MaxSim). The project includes ColBERTv2 and related tooling, with installation guidance and references to research papers and extensions.
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ColBERT (Contextualized Late Interaction over BERT) performs fine-grained, token-level max-similarity interactions
ColBERT (Late Interaction) : A multi-vector approach that keeps token-level embeddings for both queries and documents.
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