Qwen3 30B A3B Python Coder

🚀 Qwen3-30B-A3B-python-coder

本模型是基於 Qwen/Qwen3-30B-A3B 在 burtenshaw/tulu-3-sft-personas-code-no-prompt 數據集上進行微調後的版本。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="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"])

📚 詳細文檔

訓練過程

本模型採用 SFT 方法進行訓練。

框架版本

📄 許可證

該模型遵循相關許可協議，具體請參考 license 文件。

📖 引用

引用 TRL 時請使用以下 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}}
}