Qwen3 30B A3B Python Coder

🚀 Qwen3-30B-A3B-python-coder

This model is a fine - tuned version of Qwen/Qwen3 - 30B - A3B, trained on a specific dataset to enhance performance in relevant tasks.

🚀 Quick Start

Basic Usage

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"])

✨ Features

This model is a fine - tuned version of [Qwen/Qwen3 - 30B - A3B](https://huggingface.co/Qwen/Qwen3 - 30B - A3B) on the [burtenshaw/tulu - 3 - sft - personas - code - no - prompt](https://huggingface.co/datasets/burtenshaw/tulu - 3 - sft - personas - code - no - prompt) dataset. It has been trained using TRL.

🔧 Technical Details

Training procedure

This model was trained with SFT.

Framework versions

📄 License

The model is under the specified license.

📚 Documentation

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 Gallou{\'e}dec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}