Update README.md

README.md

@@ -35,7 +35,7 @@ Academic and Personal Use. You may use the Work for academic research and person
 Commercial Use. You may not use the Work for commercial purposes without prior written authorization from the Contributor(s). Any commercial use authorized by the Contributor(s) must not involve charging fees above the model inference cost without express written permission from the Contributor(s).
 Medical Application. The Work is provided for academic research purposes only and not for commercial use. It must not be used in clinical practice or in any scenario with potential medical intent without permission. The capabilities of this Traditional Chinese Medicine (TCM) Language Model, including syndrome classification and prescription generation, are experimental and not intended for clinical diagnosis or treatment. Outputs are for internal reference and testing only and should not be considered as medical advice. All medical diagnoses and treatments should be performed by experienced physicians through a standardized clinical process.
 Distribution. Redistribution of the Work or derivative works must comply with all the terms and conditions of this License.
-
+ 
 ## Training data
 
 #### 1.1 Multi-task Therapeutic Behavior Decomposition Instruction Construction Strategy
@@ -72,16 +72,16 @@ This research is for academic research use only, commercial use is not allowed w
 Data processing and annotation is one of the important steps in training the model. We sincerely welcome Traditional Chinese Medicine practitioners with strong TCM thinking and innovative spirit to join us. We will also declare corresponding data contributions. We look forward to the day when we can achieve a reliable General Artificial Intelligence for Traditional Chinese Medicine, allowing the ancient Chinese medicine to blend with modern technology and shine anew. This is also the ultimate mission of this project. If interested, please send an email to 21110860035@m.fudan.edu.cn.
 
 ## Team Introduction
-This project is jointly guided by Professor Zhang Wenqiang from Fudan University, Postdoctoral Fellow Wang Yan from Fudan University, and Professor Wang Haofen from Tongji University. The team effort includes Kang Yanlan, Chang Yang, and Fu Jiyuan from Fudan University's [ROI Lab](https://www.fudanroilab.com/), as well as Xing Haozhe in completing this project. Special thanks to the medical team from the Longhua Hospital affiliated with Shanghai University of Traditional Chinese Medicine, including Wu Sunsi, Ma Qingshan, Fang Yide, Chen Yue, Jiao Yuqi, Liu Xiyu, and Zhao Xue for their valuable data support and manual assessments.
+Led by the non-profit organization FulPhil-医哲未来 (Future Medicine Philosophy), the CMLM (Chinese Medicine Language Models) initiative on HuggingFace is dedicated to advancing healthcare AI by integrating traditional Chinese medicine with state-of-the-art machine learning. Our mission includes curating valuable medical datasets, developing AI models for medical assistance, and ensuring ethical AI use in healthcare, fostering collaboration between global experts in Chinese and Western medicine and AI.
 
 ## Citation
 If you find this work useful in your research, please cite our repository:
 ```
 @misc{CMLM-ZhongJing,
-  author = {Kang, Yanlan and Chang, Yang and Fu, Jiyuan and Wang, Haofen and Zhang, Wenqiang},
-  title = {CMLM-ZhongJing: Large Language Model are Good Story Listener},
+  author = {Liu Lin Ju Shi},
+  title = {CMLM-ZhongJing-2-1_8b: A State-of-the-Art Edge Computing Language Model for Traditional Chinese Medicine},
   year = {2023},
-  publisher = {GitHub},
+  publisher = {FulPhil-医哲未来 (Future Medicine Philosophy).},
   journal = {GitHub Repository},
   howpublished = {\url{https://github.com/pariskang/CMLM-ZhongJing}}
-}
+```