llm-course-hw2-reward-model

Model Card for reward_model_output

This model is a fine-tuned version of HuggingFaceTB/SmolLM-135M-Instruct on the HumanLLMs/Human-Like-DPO-Dataset dataset. It has been trained using TRL.

Quick start

from transformers import pipeline

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

Training procedure

This model was trained with Reward.

Framework versions

• TRL: 0.25.1
• Transformers: 4.57.1
• Pytorch: 2.8.0+cu126
• Datasets: 4.0.0
• 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}}
}