aita_qwen3_4b_nta_yta_balanced_one_ex

Model Card for aita_qwen3_4b_nta_yta_balanced_one_ex

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

text = "The capital of France is Paris."
rewarder = pipeline(model="ianyang02/aita_qwen3_4b_nta_yta_balanced_one_ex", device="cuda")
output = rewarder(text)[0]
print(output["score"])

Training procedure

<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>

This model was trained with Reward.

Framework versions

• TRL: 0.25.1
• Transformers: 4.57.1
• Pytorch: 2.7.0.dev20250224+cu126
• Datasets: 4.4.1
• Tokenizers: 0.22.1

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}}
}