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--- |
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base_model: Qwen/Qwen2-0.5B-Instruct |
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datasets: trl-lib/tldr-preference |
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library_name: transformers |
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model_name: dpo-qwen2 |
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tags: |
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- trl |
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- generated_from_trainer |
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- dpo |
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licence: license |
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--- |
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# Model Card for dpo-qwen2 |
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This model is a fine-tuned version of [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct) on the [trl-lib/tldr-preference](https://huggingface.co/datasets/trl-lib/tldr-preference) dataset. |
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It has been trained using [TRL](https://github.com/huggingface/trl). |
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## Quick start |
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```python |
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from transformers import pipeline |
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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?" |
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generator = pipeline("text-generation", model="qgallouedec/dpo-qwen2", device="cuda") |
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output = generator([{"role": "user", "content": question}], max_new_tokens=500)[0] |
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print(output["generated_text"][1]["content"]) |
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``` |
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## Training procedure |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/huggingface/huggingface/runs/gsj2o1h8) |
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This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290). |
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### Framework versions |
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- TRL: 0.12.0.dev0 |
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- Transformers: 4.45.0.dev0 |
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- Pytorch: 2.4.1 |
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- Datasets: 3.0.0 |
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- Tokenizers: 0.19.1 |
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## Citations |
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Cite DPO as: |
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```bibtex |
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@inproceedings{rafailov2023direct, |
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title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}}, |
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author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn}, |
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year = 2023, |
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booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023}, |
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url = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html}, |
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editor = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine}, |
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} |
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``` |
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Cite TRL as: |
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```bibtex |
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@misc{vonwerra2022trl, |
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title = {{TRL: Transformer Reinforcement Learning}}, |
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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}, |
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year = 2020, |
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journal = {GitHub repository}, |
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publisher = {GitHub}, |
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howpublished = {\url{https://github.com/huggingface/trl}} |
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} |
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``` |
