metadata
base_model: Qwen/Qwen3-4B-Instruct-2507
library_name: peft
model_name: v2b_n241
tags:
- base_model:adapter:Qwen/Qwen3-4B-Instruct-2507
- lora
- sft
- transformers
- trl
licence: license
pipeline_tag: text-generation
Model Card for v2b_n241
This model is a fine-tuned version of Qwen/Qwen3-4B-Instruct-2507. 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="cuda")
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 0.20.0
- TRL: 1.10.0
- Transformers: 5.15.0
- Pytorch: 2.13.0
- Datasets: 5.0.1
- Tokenizers: 0.22.2
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}
}