| license: mit | |
| language: | |
| - en | |
| ## Example Usage | |
| ```python | |
| from transformers import AutoTokenizer, T5ForConditionalGeneration | |
| tokenizer = AutoTokenizer.from_pretrained("QizhiPei/biot5-plus-large") | |
| model = T5ForConditionalGeneration.from_pretrained('QizhiPei/biot5-plus-large') | |
| ``` | |
| ## References | |
| For more information, please refer to our paper and GitHub repository. | |
| Paper: [BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning](https://arxiv.org/abs/2402.17810) | |
| GitHub: [BioT5+](https://github.com/QizhiPei/BioT5) | |
| Authors: *Qizhi Pei, Lijun Wu, Kaiyuan Gao, Xiaozhuan Liang, Yin Fang, Jinhua Zhu, Shufang Xie, Tao Qin, and Rui Yan* |