metadata
library_name: transformers
model_name: ppo_tldr
tags:
- generated_from_trainer
- ppo
- trl
licence: license
Model Card for ppo_tldr
This model is a fine-tuned version of None. 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="sergiopaniego/ppo_tldr", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
Training procedure
This model was trained with PPO, a method introduced in Fine-Tuning Language Models from Human Preferences.
Framework versions
- TRL: 0.28.0.dev0
- Transformers: 4.57.6
- Pytorch: 2.9.0
- Datasets: 4.0.0
- Tokenizers: 0.22.1
Citations
Cite PPO as:
@article{mziegler2019fine-tuning,
title = {{Fine-Tuning Language Models from Human Preferences}},
author = {Daniel M. Ziegler and Nisan Stiennon and Jeffrey Wu and Tom B. Brown and Alec Radford and Dario Amodei and Paul F. Christiano and Geoffrey Irving},
year = 2019,
eprint = {arXiv:1909.08593}
}
Cite TRL as:
@software{vonwerra2020trl,
title = {{TRL: Transformers Reinforcement Learning}},
author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
license = {Apache-2.0},
url = {https://github.com/huggingface/trl},
year = {2020}
}