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README.md

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 This model was converted to GGUF format from [`FreedomIntelligence/HuatuoGPT-o1-7B`](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-7B) 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-o1-7B) 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. 
-
-
-For more information, visit our GitHub repository: 
-https://github.com/FreedomIntelligence/HuatuoGPT-o1.
-
-
-		Usage
-	
-
-
-
-You can use HuatuoGPT-o1-7B in the same way as Qwen2.5-7B-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-o1-7B",torch_dtype="auto",device_map="auto")
-tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/HuatuoGPT-o1-7B")
-
-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)