qwen3-0.6b-RM-hs2-validation

Model Card for qwen3-0.6b-RM-hs2-validation

This model is a fine-tuned version of Qwen/Qwen3-0.6B-Base. It has been trained using TRL.

Quick start

from transformers import pipeline

text = "The capital of France is Paris."
rewarder = pipeline(model="LeonhardP/qwen3-0.6b-RM-hs2-validation", device="cuda")
output = rewarder(text)[0]
print(output["score"])

Training procedure

This model was trained with Reward.

Framework versions

• TRL: 0.25.1
• Transformers: 4.57.3
• Pytorch: 2.9.0+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}}
}