Model Card for pythia-1b-online-dpo-HH-merge-rewardmodel-duplicated
This model is a fine-tuned version of XueyingJia/pythia-1b-sft-HH-3-merge on the XueyingJia/online_dpo_repo 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="XueyingJia/pythia-1b-online-dpo-HH-merge-rewardmodel-duplicated", 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 Online DPO, a method introduced in Direct Language Model Alignment from Online AI Feedback.
Framework versions
- TRL: 0.13.0.dev0
- Transformers: 4.46.3
- Pytorch: 2.5.1
- Datasets: 3.1.0
- Tokenizers: 0.20.3
Citations
Cite Online DPO as:
@article{guo2024direct,
title = {{Direct Language Model Alignment from Online AI Feedback}},
author = {Shangmin Guo and Biao Zhang and Tianlin Liu and Tianqi Liu and Misha Khalman and Felipe Llinares and Alexandre Ram{'{e}} and Thomas Mesnard and Yao Zhao and Bilal Piot and Johan Ferret and Mathieu Blondel},
year = 2024,
eprint = {arXiv:2402.04792}
}
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}}
}
Model tree for XueyingJia/pythia-1b-online-dpo-HH-merge-rewardmodel-duplicated
Base model
XueyingJia/pythia-1b-sft-HH-3-merge