ncbi/MedCPT-Query-Encoder
feature-extraction model by ncbi
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Model card & documentation
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MedCPT generates embeddings of biomedical texts that can be used for semantic search (dense retrieval). The model contains two encoders: This repo contains the MedCPT Query Encoder. MedCPT has been pre-trained by an unprecedented scale of 255M query-article pairs from PubMed search logs, and has been shown to achieve state-of-the-art performance on several zero-shot biomedical IR datasets. In general, there are three use cases: For more details, please check out our paper (Bioinformatics, 2023). Please note that the released version is slightly different from the version reported in the paper. The output will be: These embeddings are also in the same space as those generated by the MedCPT article encoder. We have provided the embeddings of all PubMed articles generated by the MedCPT article encoder at https://ftp.ncbi.nlm.nih.gov/pub/lu/MedCPT/pubmedembeddings/. You can simply download these embeddings to search PubMed with your query. This work was supported by the Intramural Research Programs of the…
Read the full model card ↗ · Preview checked 2026-10-27T18:45:36.081Z
Inside the original model card — Document outline
- MedCPT Introduction
- Case 1. Using the MedCPT Query Encoder
- Case 2. Semantically searching PubMed with your query
- Acknowledgments
- Disclaimer
- Citation
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Model overview
ncbi/MedCPT-Query-Encoder is a feature-extraction model repository published by ncbi on Hugging Face. The source reports the transformers library.
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Model facts
- Task
- feature-extraction
- Library
- transformers
- Recent downloads (30 days)
- 98,849
- Cumulative likes
- 66
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 109,482,240
- Architecture
- BertModel
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2023-10-24T22:57:48.000Z
- Last modified
- 2023-12-03T00:45:30.000Z
Compatibility and lineage
Language coverage was not reported.
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