Triangle104/HuatuoGPT-o1-8B-Q4_K_S-GGUF

This model was converted to GGUF format from FreedomIntelligence/HuatuoGPT-o1-8B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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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}, }

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Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Triangle104/HuatuoGPT-o1-8B-Q4_K_S-GGUF --hf-file huatuogpt-o1-8b-q4_k_s.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/HuatuoGPT-o1-8B-Q4_K_S-GGUF --hf-file huatuogpt-o1-8b-q4_k_s.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Triangle104/HuatuoGPT-o1-8B-Q4_K_S-GGUF --hf-file huatuogpt-o1-8b-q4_k_s.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/HuatuoGPT-o1-8B-Q4_K_S-GGUF --hf-file huatuogpt-o1-8b-q4_k_s.gguf -c 2048