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--- |
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inference: false |
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license: mit |
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license_link: https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- nlp |
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- code |
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- biology |
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- medical |
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--- |
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## Model Summary |
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MedPhi-2 is a Phi-2, **2.7 billion** parameters, further trained for the biomedical domain. |
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It was proposed in MedExQA paper. |
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<h1> 🧑⚕️ MedExQA </h1> |
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<h3> Medical Question Answering Benchmark with Multiple Explanations </h3> |
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<p> |
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📄 <a href="https://arxiv.org/abs/2406.06331" target="_blank">Paper</a> • ⏬ <a href="https://huggingface.co/datasets/bluesky333/MedExQA" target="_blank">Dataset</a> • ⚕️ <a href="https://huggingface.co/bluesky333/medphi2" target="_blank">MedPhi2</a><br> |
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</p> |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Model type:** Clinical LLM (Large Language Model) |
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- **Language(s) (NLP):** English |
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- **License:** [MIT license](https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE) |
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- **Finetuned from model [optional]:** Phi-2 |
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## Citation |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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``` |
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@article{kim2024medexqa, |
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title={MedExQA: Medical Question Answering Benchmark with Multiple Explanations}, |
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author={Kim, Yunsoo and Wu, Jinge and Abdulle, Yusuf and Wu, Honghan}, |
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journal={arXiv e-prints}, |
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pages={arXiv--2406}, |
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year={2024} |
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} |
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``` |
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