Openr1 Qwen 7B SFT Instruct

🚀 OpenR1-Qwen-7B-SFT-Instruct

本模型是基於Qwen/Qwen2.5-7B-Instruct在open-r1/OpenR1-Math-220k數據集上進行微調得到的版本。它使用TRL進行訓練。

🚀 快速開始

from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="ZMC2019/OpenR1-Qwen-7B-SFT-Instruct", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

🔧 技術細節

訓練過程

本模型使用SFT進行訓練。

框架版本

• TRL: 0.16.0.dev0
• Transformers: 4.49.0
• Pytorch: 2.5.1
• Datasets: 3.3.2
• Tokenizers: 0.21.0

📄 許可證

該項目遵循指定的許可證，詳情請查看 license 文件。

📚 引用

引用TRL時請使用以下格式：

@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}}
}

模型信息表格