Taiyi 2 (太一2): A Bilingual (Chinese and English) Fine-Tuned Large Language Model for Diverse Biomedical Tasks
0
8 commits
2 linked in READMEs
updated Apr 18, 2026
This is the model of Taiyi2 using GLM4-9B as the base model, developed by DUTIR lab.
With the rapid development of deep learning technology, large language models (LLMs) like ChatGPT and DeepSeek have made significant progress in the field of natural language processing. In the biomedical domain, large language models can facilitate communication between doctors and patients, provide useful medical information, and hold great potential in areas such as clinical decision support, biomedical knowledge discovery, drug development, and personalized treatment planning. Therefore, this project focuses on developing a multilingual, multi-task large language model tailored for various biomedical scenarios, aiming to achieve high performance with low resource consumption. In October 2023, we released the initial version of a bilingual Chinese-English biomedical large language model—Taiyi. Research efforts have continued, and the development of Taiyi 2 has now been completed, with the model being open-sourced.
Compared to the Taiyi 1, Taiyi 2 introduces further research and improvements in areas such as the model backbone, data instructions, and task-specific instructions. The main updates are as follows:
The environment configuration we used for training and testing is as follows:
torch==2.4.0
ms_swift==2.6.1
transformers==4.44.0
transformers-stream-generator==0.0.5
vllm==0.6.0
vllm-flash-attn==2.6.1
To install all dependencies automatically using the command:
$ pip install -r requirements.txt
Referring to the taiyi2_chat.py file, it is recommended to use a GPU to ensure faster inference speed.
If you use the repository of this project, please cite it.
@article{Taiyi,
title="{Taiyi: A Bilingual Fine-Tuned Large Language Model for Diverse Biomedical Tasks}",
author={Ling Luo, Jinzhong Ning, Yingwen Zhao, Zhijun Wang, Zeyuan Ding, Peng Chen, Weiru Fu, Qinyu Han, Guangtao Xu, Yunzhi Qiu, Dinghao Pan, Jiru Li, Hao Li, Wenduo Feng, Senbo Tu, Yuqi Liu, Zhihao Yang, Jian Wang, Yuanyuan Sun, Hongfei Lin},
journal={Journal of the American Medical Informatics Association},
year={2024},
doi = {10.1093/jamia/ocae037},
url = {https://doi.org/10.1093/jamia/ocae037},
}
8 commits
Taiyi 2 (太一2): A Bilingual (Chinese and English) Fine-Tuned Large Language Model for Diverse Biomedical Tasks
0
8 commits
2 linked in READMEs
updated Apr 18, 2026
This is the model of Taiyi2 using GLM4-9B as the base model, developed by DUTIR lab.
With the rapid development of deep learning technology, large language models (LLMs) like ChatGPT and DeepSeek have made significant progress in the field of natural language processing. In the biomedical domain, large language models can facilitate communication between doctors and patients, provide useful medical information, and hold great potential in areas such as clinical decision support, biomedical knowledge discovery, drug development, and personalized treatment planning. Therefore, this project focuses on developing a multilingual, multi-task large language model tailored for various biomedical scenarios, aiming to achieve high performance with low resource consumption. In October 2023, we released the initial version of a bilingual Chinese-English biomedical large language model—Taiyi. Research efforts have continued, and the development of Taiyi 2 has now been completed, with the model being open-sourced.
Compared to the Taiyi 1, Taiyi 2 introduces further research and improvements in areas such as the model backbone, data instructions, and task-specific instructions. The main updates are as follows:
The environment configuration we used for training and testing is as follows:
torch==2.4.0
ms_swift==2.6.1
transformers==4.44.0
transformers-stream-generator==0.0.5
vllm==0.6.0
vllm-flash-attn==2.6.1
To install all dependencies automatically using the command:
$ pip install -r requirements.txt
Referring to the taiyi2_chat.py file, it is recommended to use a GPU to ensure faster inference speed.
If you use the repository of this project, please cite it.
@article{Taiyi,
title="{Taiyi: A Bilingual Fine-Tuned Large Language Model for Diverse Biomedical Tasks}",
author={Ling Luo, Jinzhong Ning, Yingwen Zhao, Zhijun Wang, Zeyuan Ding, Peng Chen, Weiru Fu, Qinyu Han, Guangtao Xu, Yunzhi Qiu, Dinghao Pan, Jiru Li, Hao Li, Wenduo Feng, Senbo Tu, Yuqi Liu, Zhihao Yang, Jian Wang, Yuanyuan Sun, Hongfei Lin},
journal={Journal of the American Medical Informatics Association},
year={2024},
doi = {10.1093/jamia/ocae037},
url = {https://doi.org/10.1093/jamia/ocae037},
}
8 commits