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+ ---
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+ license: mit
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+ datasets:
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+ - QizhiPei/BioT5_finetune_dataset
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+ language:
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+ - en
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+ ---
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+ ## Example Usage
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+ ```python
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+ from transformers import AutoTokenizer, T5ForConditionalGeneration
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+
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+ tokenizer = AutoTokenizer.from_pretrained("QizhiPei/biot5-base-peer-solubility", model_max_length=512)
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+ model = T5ForConditionalGeneration.from_pretrained('QizhiPei/biot5-base-peer-solubility')
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+ ```
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+
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+ ## References
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+ For more information, please refer to our paper and GitHub repository.
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+
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+ Paper: [BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations](https://arxiv.org/abs/2310.07276)
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+
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+ GitHub: [BioT5](https://github.com/QizhiPei/BioT5)
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+
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+ Authors: *Qizhi Pei, Wei Zhang, Jinhua Zhu, Kehan Wu, Kaiyuan Gao, Lijun Wu, Yingce Xia, and Rui Yan*