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README.md
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# BioMedGPT-LM-7B
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### Training Details
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* Cutoff length: 2048
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* Learning rate: 2e-5
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(PMC)-ID and PubMed ID as criteria.
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### Model Developers
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PharMolix
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### How to Use
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BioMedGPT-LM-7B is a part of **[BioMedGPT-10B](https://github.com/BioFM/OpenBioMed)**, an open-source version of BioMedGPT. BioMedGPT is a multimodal generative pre-trained transformer (GPT) for biomedicine, which bridges the natural language modality and diverse biomed-
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ical data modalities via a single GPT model. BioMedGPT aligns different biological modalities with the text modality via BioMedGPT-LM. The details of BioMedGPT-10B and BioMedGPT-LM-7B can be found in the [technical report]().
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
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**Intended Use Cases**
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# BioMedGPT-LM-7B
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**BioMedGPT-LM-7B** is the first large generative language model based on Llama2 in the biomedical domain.
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It was fine-tuned from the Llama2-7B-Chat with millions of biomedical papers from the [S2ORC corpus](https://github.com/allenai/s2orc/blob/master/README.md).
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Through further fine-tuning, BioMedGPT-LM-7B outperforms or is on par with human and significantly larger general-purpose foundation models on several biomedical QA benchmarks.
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### Training Details
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* Cutoff length: 2048
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* Learning rate: 2e-5
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BioMedGPT-LM-7B is finetuned on over 26 billion tokens highly pertinent to the field of biomedicine.
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The fine-tuning data are extracted from 5.5 million biomedical papers in S2ORC data using PubMed Central (PMC)-ID and PubMed ID as criteria.
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### Model Developers
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PharMolix
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### How to Use
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BioMedGPT-LM-7B is the generative language model of **[BioMedGPT-10B](https://github.com/BioFM/OpenBioMed)**, an open-source version of BioMedGPT.
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BioMedGPT is an open multimodal generative pre-trained transformer (GPT) for biomedicine, which bridges the natural language modality and diverse biomedical data modalities via large generative language models.
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More technical details of BioMedGPT-LM-7B, BioMedGPT-10B, and BioMedGPT can be found in the [technical report](https://pan.baidu.com/s/1iAMBkuoZnNAylhopP5OgEg?pwd=7a6b).
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
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**Intended Use Cases**
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