Model Card for llama-1b-reward-tldr

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the trl-internal-testing/tldr-preference-trl-style dataset. 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="agsidd10/llama-1b-reward-tldr", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

👁 Visualize in Weights & Biases

This model was trained with Reward.

Framework versions

• TRL: 0.16.0.dev0
• Transformers: 4.49.0
• Pytorch: 2.5.1
• Datasets: 4.0.0
• Tokenizers: 0.21.4

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 Gallouédec},
 year = 2020,
 journal = {GitHub repository},
 publisher = {GitHub},
 howpublished = {\url{https://github.com/huggingface/trl}}
}

Base model

meta-llama/Llama-3.2-1B

(925)