Update README.md

README.md

@@ -1,3 +1,65 @@
 ---
 license: mit
+language:
+- en
+metrics:
+- f1
+tags:
+- medical
 ---
+
+# MentaLLaMA-chat-13B
+
+MentaLLaMA-chat-13B is part of the [MentaLLaMA](https://github.com/SteveKGYang/MentalLLaMA) project, the first open-source large language model (LLM) series for 
+interpretable mental health analysis with instruction-following capability.
+The model is expected to make complex mental health analyses for various mental health conditions and give reliable explanations for each of its predictions.
+It is fine-tuned on the IMHI dataset with 75K high-quality natural language instructions to boost its performance in downstream tasks.
+We perform a comprehensive evaluation on the IMHI benchmark with 20K test samples. The result shows that MentalLLaMA approaches state-of-the-art discriminative
+methods in correctness and generates high-quality explanations.
+
+## Other Models in MentaLLaMA
+
+In addition to MentaLLaMA-chat-13B, the MentaLLaMA project includes another model: MentaLLaMA-chat-7B, MentalBART, MentalT5.
+
+- **MentaLLaMA-chat-7B**: This model 
+
+- **MentalBART**: This model 
+
+- **MentalT5**: This model 
+
+## Usage
+
+You can use the MentaLLaMA-chat-13B model in your Python project with the Hugging Face Transformers library. Here is a simple example of how to load the model:
+
+```python
+from transformers import LlamaTokenizer, LlamaForCausalLM
+tokenizer = LlamaTokenizer.from_pretrained('klyang/MentaLLaMA-chat-13B')
+model = LlamaForCausalLM.from_pretrained('klyang/MentaLLaMA-chat-13B', device_map='auto')
+```
+
+In this example, LlamaTokenizer is used to load the tokenizer, and LlamaForCausalLM is used to load the model. The `device_map='auto'` argument is used to automatically
+use the GPU if it's available.
+
+## License
+
+MentaLLaMA-chat-13B is licensed under MIT. For more details, please see the MIT file.
+
+## About
+
+This model is part of the MentaLLaMA project.
+For more information, you can visit the [MentaLLaMA](https://github.com/SteveKGYang/MentalLLaMA) project on GitHub.
+
+## Citation
+
+If you use MentaLLaMA-chat-7B in your work, please cite our paper:
+
+```bibtex
+@misc{yang2023mentalllama,
+      title={MentalLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models}, 
+      author={Kailai Yang and Tianlin Zhang and Ziyan Kuang and Qianqian Xie and Sophia Ananiadou},
+      year={2023},
+      eprint={2309.13567},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```