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FreedomIntelligence
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Model Details
Model Provider
FreedomIntelligence
Model Tree
Qwen/Qwen3-32B
Input Modalities
Output Modalities
Supported Functionality
HuatuoGPT-3 is an open-source medical LLM trained with SeedRL, an RL-only domain adaptation paradigm that transforms a base model into a medical expert in a single RL stage.
For more information, visit our GitHub repository: https://github.com/FreedomIntelligence/HuatuoGPT-3
[!IMPORTANT] HuatuoGPT-3-32B is set to thinking mode by default. The output contains a
<think>...</think>reasoning block followed by the final response after</think>.
| Model | Description | Backbone | Link |
|---|---|---|---|
| HuatuoGPT-3-32B | 32B medical LLM trained with SeedRL | Qwen3-32B | HF Link |
| HuatuoGPT-3-8B | 8B medical LLM trained with SeedRL | Qwen3-8B-Base | HF Link |
| HuatuoGPT-3-7B-Pangu | 7B medical LLM trained with SeedRL | openPangu-Embedded-7B | HF Link |
You can use HuatuoGPT-3-8B in the same way as Qwen3-32B. You can deploy it with tools like vLLM or SGLang, or perform direct inference:
python
from transformers import AutoModelForCausalLM, AutoTokenizermodel_name = "FreedomIntelligence/HuatuoGPT-3-32B"tokenizer = AutoTokenizer.from_pretrained(model_name)model = AutoModelForCausalLM.from_pretrained(model_name,torch_dtype="auto",device_map="auto")messages = [{"role": "user", "content": "A patient has fever, cough, and shortness of breath. What should be considered first?"}]text = tokenizer.apply_chat_template(messages,tokenize=False,add_generation_prompt=True)inputs = tokenizer([text], return_tensors="pt").to(model.device)outputs = model.generate(**inputs, max_new_tokens=4096)print(tokenizer.decode(outputs[0], skip_special_tokens=True))
bibtex
@inproceedings{huatuogpt3,title={OnePO: Direct One-stage Policy Optimization for SFT-free Domain Adaptation},author={Chen, Junying and Xie, Xinyuan and Li, Ziniu and Wang, Benyou},booktitle={Proceedings of the 43rd International Conference on Machine Learning},series={Proceedings of Machine Learning Research},volume={306},year={2026}}