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utahnlp/tevatron-elastic-bert-retriever-starbucks
tevatron-elastic-bert-retriever-starbucks is a feature extraction model from utahnlp. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as apache-2.0.
A retriever trained with Tevatron-Elastic, which trains one checkpoint to serve many operating points along the depth / width / token compression axes. This checkpoint is an elastic depth×width schedule (2D Matryoshka…
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From the Hugging Face model README
A retriever trained with Tevatron-Elastic, which trains one checkpoint to serve many operating points along the depth / width / token compression axes. This checkpoint is an elastic depth×width schedule (2D Matryoshka, Starbucks-style).
google-bert/bert-base-uncasedquery:/passage: prefixes.Full-point BEIR-15 nDCG@10: 0.448.
Load with the Tevatron-Elastic framework and select an operating point with prune_to /
encode_at; see the repository for usage. Part of a release of 20 checkpoints (3 backbones,
retrieval and reranking, all compression axes) accompanying the Tevatron-Elastic paper. Reported as
a reproducibility resource, not a state-of-the-art claim.