Update README.md

README.md

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 This model was converted to GGUF format from [`FreedomIntelligence/HuatuoGPT-o1-8B`](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-8B) for more details on the model.
 
+---
+Model details:
+-
+HuatuoGPT-o1 is a medical LLM designed for advanced medical reasoning. It generates a complex thought process, reflecting and refining its reasoning, before providing a final response.
+
+Usage
+You can use HuatuoGPT-o1 in the same way as Llama-3.1-8B-Instruct. You can deploy it with tools like vllm or Sglang, or perform direct inference:
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/HuatuoGPT-o1-8B",torch_dtype="auto",device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/HuatuoGPT-o1-8B")
+
+input_text = "How to stop a cough?"
+messages = [{"role": "user", "content": input_text}]
+
+inputs = tokenizer(tokenizer.apply_chat_template(messages, tokenize=False,add_generation_prompt=True
+), return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=2048)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+
+HuatuoGPT-o1 adopts a thinks-before-it-answers approach, with outputs formatted as:
+
+## Thinking
+[Reasoning process]
+
+## Final Response
+[Output]
+
+📖 Citation
+@misc{chen2024huatuogpto1medicalcomplexreasoning,
+      title={HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs}, 
+      author={Junying Chen and Zhenyang Cai and Ke Ji and Xidong Wang and Wanlong Liu and Rongsheng Wang and Jianye Hou and Benyou Wang},
+      year={2024},
+      eprint={2412.18925},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2412.18925}, 
+}
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)