🚀 Qwen3-30B-A3B-python-coder

本模型是基于 Qwen/Qwen3-30B-A3B 在 burtenshaw/tulu-3-sft-personas-code-no-prompt 数据集上进行微调后的版本。它使用 TRL 进行训练。

🚀 快速开始

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="burtenshaw/Qwen3-30B-A3B-python-coder", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

📚 详细文档

训练过程

本模型采用 SFT 方法进行训练。

框架版本

📄 许可证

该模型遵循相关许可协议，具体请参考 license 文件。

📖 引用

引用 TRL 时请使用以下 BibTeX 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 Gallou{\'e}dec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}