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  - [MedCPT Query Encoder](https://huggingface.co/ncbi/MedCPT-Query-Encoder): compute the embeddings of short texts (e.g., questions, search queries, sentences).
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  - [MedCPT Article Encoder](https://huggingface.co/ncbi/MedCPT-Article-Encoder): compute the embeddings of articles (e.g., PubMed titles & abstracts).
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- **MedCPT has been pre-trained by an unprecedented scale of 255M query-article pairs from PubMed search logs**. In general, there are three use cases:
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  1. Query-to-article search with both encoders.
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  2. Query representation for clustering or query-to-query search with the [query encoder)[https://huggingface.co/ncbi/MedCPT-Query-Encoder].
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  3. Article representation for clustering or article-to-article search with the (prticle encoder)[https://huggingface.co/ncbi/MedCPT-Article-Encoder].
@@ -54,16 +54,17 @@ tensor([[ 0.0413, 0.0084, -0.0491, ..., -0.4963, -0.3830, -0.3593],
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  [-0.3412, 0.1521, -0.0946, ..., 0.0952, 0.1660, -0.0902]])
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  torch.Size([3, 768])
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  ```
 
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- ## Acknowledgments
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  This work was supported by the Intramural Research Programs of the National Institutes of Health, National Library of Medicine.
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- ## Disclaimer
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  This tool shows the results of research conducted in the Computational Biology Branch, NCBI/NLM. The information produced on this website is not intended for direct diagnostic use or medical decision-making without review and oversight by a clinical professional. Individuals should not change their health behavior solely on the basis of information produced on this website. NIH does not independently verify the validity or utility of the information produced by this tool. If you have questions about the information produced on this website, please see a health care professional. More information about NCBI's disclaimer policy is available.
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- ## Citation
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  If you find this repo helpful, please cite MedCPT by:
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  - [MedCPT Query Encoder](https://huggingface.co/ncbi/MedCPT-Query-Encoder): compute the embeddings of short texts (e.g., questions, search queries, sentences).
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  - [MedCPT Article Encoder](https://huggingface.co/ncbi/MedCPT-Article-Encoder): compute the embeddings of articles (e.g., PubMed titles & abstracts).
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+ **MedCPT has been pre-trained by an unprecedented scale of 255M query-article pairs from PubMed search logs**, and has been shown to achieve the state-of-the-art performance on several zero-shot biomedical IR datasets. In general, there are three use cases:
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  1. Query-to-article search with both encoders.
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  2. Query representation for clustering or query-to-query search with the [query encoder)[https://huggingface.co/ncbi/MedCPT-Query-Encoder].
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  3. Article representation for clustering or article-to-article search with the (prticle encoder)[https://huggingface.co/ncbi/MedCPT-Article-Encoder].
 
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  [-0.3412, 0.1521, -0.0946, ..., 0.0952, 0.1660, -0.0902]])
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  torch.Size([3, 768])
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  ```
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+ These embeddings are also in the same space as those generated by the MedCPT article encoder.
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+ # Acknowledgments
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  This work was supported by the Intramural Research Programs of the National Institutes of Health, National Library of Medicine.
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+ # Disclaimer
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  This tool shows the results of research conducted in the Computational Biology Branch, NCBI/NLM. The information produced on this website is not intended for direct diagnostic use or medical decision-making without review and oversight by a clinical professional. Individuals should not change their health behavior solely on the basis of information produced on this website. NIH does not independently verify the validity or utility of the information produced by this tool. If you have questions about the information produced on this website, please see a health care professional. More information about NCBI's disclaimer policy is available.
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+ # Citation
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  If you find this repo helpful, please cite MedCPT by:
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