Model Card for Qwen2.5-1.5B-R1-Distill-Medical

This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct. It has been trained using TRL.

Quick start

from transformers import pipeline

generator = pipeline("text-generation", model="Mingsmilet/Qwen2.5-1.5B-R1-Distill-Medical", device="cuda")
question = "根据以下临床表现：短气息促，动则为甚，吸气不利，腰酸腿软，脑转耳鸣，劳累后哮喘易发，面色苍白，舌淡苔白，质胖嫩，脉象沉细，治疗哪一种中药方剂最为适合？"
output = generator([{"role": "user", "content": question}], max_new_tokens=4096, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

This model was trained with SFT.

Framework versions

• TRL: 0.15.2
• Transformers: 4.49.0
• Pytorch: 2.5.1
• Datasets: 3.3.2
• Tokenizers: 0.21.0

Citations

Cite TRL as:

@misc{vonwerra2022trl,
    title        = {{TRL: Transformer Reinforcement Learning}},
    author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
    year         = 2020,
    journal      = {GitHub repository},
    publisher    = {GitHub},
    howpublished = {\url{https://github.com/huggingface/trl}}
}