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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 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
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3. Article representation for clustering or article-to-article search with the
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For more details, please check out our [paper](https://arxiv.org/abs/2307.00589) (Bioinformatics, 2023).
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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 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 [article encoder](https://huggingface.co/ncbi/MedCPT-Article-Encoder).
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For more details, please check out our [paper](https://arxiv.org/abs/2307.00589) (Bioinformatics, 2023).
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