初始化项目，由ModelHub XC社区提供模型

Model: linjc16/Panacea-7B-Chat
Source: Original Platform

README.md

@@ -0,0 +1,46 @@
+---
+license: apache-2.0
+language:
+- en
+base_model:
+- mistralai/Mistral-7B-v0.1
+pipeline_tag: text-generation
+tags:
+- clinical trial
+- foundation model
+---
+
+# Model Card for Panacea-7B-Chat
+The Panacea-7B-Chat is a foundation model for clinical trial search, summarization, design, and recruitment. It was equipped with clinical knowledge by being trained on 793,279 clinical trial design documents
+worldwide and 1,113,207 clinical study papers. It shows superior performances than various open-sourced LLMs and medical LLMs on clinical trial tasks.
+
+For full details of this model please read our [paper](https://arxiv.org/abs/2407.11007).
+
+## Model Training
+Panacea is trained from [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1). The training of Panacea consists of an alignment step and an instruction-tuning step.
+* Alignment step: continued pre-training on a large collection of trial documents and trial-related scientific papers. This step adapts Panacea to the vocabulary commonly used in clinical trials.
+* Instruction-tuning step: further enables Panacea to comprehend the user explanation of the task definition and the output requirement.
+
+Load the model in the following way (same as Mistral):
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = 'linjc16/Panacea-7B-Chat'
+
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+```
+
+## Citation
+If you find our paper or models helpful, please consider cite as follows:
+
+```bibtex
+@article{lin2024panacea,
+  title={Panacea: A foundation model for clinical trial search, summarization, design, and recruitment},
+  author={Lin, Jiacheng and Xu, Hanwen and Wang, Zifeng and Wang, Sheng and Sun, Jimeng},
+  journal={arXiv preprint arXiv:2407.11007},
+  year={2024}
+}
+```