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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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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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## References |
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For more information, please refer to our paper and GitHub repository. |
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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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GitHub: [BioT5](https://github.com/QizhiPei/BioT5) |
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Authors: *Qizhi Pei, Wei Zhang, Jinhua Zhu, Kehan Wu, Kaiyuan Gao, Lijun Wu, Yingce Xia, and Rui Yan* |
