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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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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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- [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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**This repo contains the MedCPT Query Encoder.**
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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 (prticle encoder)[https://huggingface.co/ncbi/MedCPT-Article-Encoder].
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