Model Card for teaching-assistant-0.6B-rm

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

Quick start

from transformers import pipeline

text = "The capital of France is Paris."
rewarder = pipeline(model="aracape/teaching-assistant-0.6B-rm", device="cuda")
output = rewarder(text)[0]
print(output["score"])

Training procedure

This model was trained with Reward.

Framework versions

• TRL: 0.24.0
• Transformers: 4.57.0
• Pytorch: 2.8.0
• Datasets: 4.1.1
• 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}}
}