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="Eehan/Qwen2.5-1.5B-drpo-lora-flip-hh", 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 DRPO, a method introduced in Doubly Robust Alignment for Large Language Models.

Framework versions

TRL: 0.19.1
Transformers: 4.54.0
Pytorch: 2.7.1
Datasets: 4.0.0
Tokenizers: 0.21.2

Citations

Cite DRPO as:

bibtex

@article{xu2024doubly,
    title        = {{Doubly Robust Alignment for Large Language Models}},
    author       = {Xu, Erhan and Ye, Kai and Zhou, Hongyi and Zhu, Luhan and Quinzan, Francesco and Shi, Chengchun},
    year         = 2025,
    journal      = {arXiv preprint arXiv:2506.01183}
}

Cite TRL as:

bibtex

@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}}
}