quy223/qwen25-coder-nl2code-lora
0
Model Card for lora-adapter
This model is a fine-tuned version of Qwen/Qwen2.5-Coder-0.5B-Instruct. It has been trained using TRL.
Quick start
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="None", device_map="auto")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])Training procedure
This model was trained with SFT.
Framework versions
- PEFT 0.21.2
- TRL: 1.14.2
- Transformers: 5.19.0
- Pytorch: 2.10.0+cu128
- Datasets: 5.1.0
- Tokenizers: 0.23.2
Citations
Cite TRL as:
@software{vonwerra2020trl,
title = {{TRL: Transformers Reinforcement Learning}},
author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
license = {Apache-2.0},
url = {https://github.com/huggingface/trl},
year = {2020}
}