初始化项目，由ModelHub XC社区提供模型

Model: medicalai/ClinicalGPT-R1-Qwen-7B-EN-preview
Source: Original Platform

README.md

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+---
+license: afl-3.0
+base_model:
+- Qwen/Qwen2.5-7B-Instruct
+pipeline_tag: text-generation
+tags:
+- medical
+---
+
+
+# Instruction
+For more information, visit our GitHub repository: https://github.com/medfound/medfound
+
+
+# Quickstart
+``` python
+import pandas as pd
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_path = "medicalai/ClinicalGPT-R1-Qwen-7B-EN-preview"
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForCausalLM.from_pretrained(model_path, device_map="auto")
+data = pd.read_json('data/test.zip', lines=True).iloc[1]
+
+prompt = f"{data["context"]}\n\nPlease provide a detailed and comprehensive diagnostic analysis of this medical record, and give the diagnostic results.\n"
+messages = [
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+
+input_ids = tokenizer([text], return_tensors="pt").to(model.device)
+output_ids = model.generate(**input_ids, max_new_tokens=2048, temperature=0.7, do_sample=True).to(model.device)
+generated_text = tokenizer.decode(output_ids[0,len(input_ids[0]):], skip_special_tokens=True)
+print("Generated Output:\n", generated_text)
+```
+
+# Citation
+If you find our work helpful, feel free to give us a cite.
+
+```
+Wang, G., Liu, X., Liu, H., Yang, G. et al. A Generalist Medical Language Model for Disease Diagnosis Assistance. Nat Med (2025). https://doi.org/10.1038/s41591-024-03416-6
+```