| ---
|
| base_model: Qwen/Qwen2.5-3B-Instruct
|
| library_name: transformers
|
| model_name: dpo_python_code
|
| tags:
|
| - generated_from_trainer
|
| - trl
|
| - dpo
|
| licence: license
|
| language:
|
| - zho
|
| - eng
|
| - fra
|
| - spa
|
| - por
|
| - deu
|
| - ita
|
| - rus
|
| - jpn
|
| - kor
|
| - vie
|
| - tha
|
| - ara
|
| ---
|
|
|
| # Model Card for dpo_python_code
|
|
|
| This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct).
|
| It has been trained using [TRL](https://github.com/huggingface/trl).
|
|
|
| ## Quick start
|
|
|
| ```python
|
| 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="gowthamvenkat/dpo_python_code", 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 DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
|
|
|
| ### Framework versions
|
|
|
| - TRL: 0.12.1
|
| - Transformers: 4.46.3
|
| - Pytorch: 2.2.1+cu121
|
| - Datasets: 3.1.0
|
| - Tokenizers: 0.20.3
|
|
|
| ## Citations
|
|
|
| Cite DPO as:
|
|
|
| ```bibtex
|
| @inproceedings{rafailov2023direct,
|
| title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}},
|
| author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn},
|
| year = 2023,
|
| 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},
|
| url = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html},
|
| editor = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine},
|
| }
|
| ```
|
|
|
| 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 Gallouédec},
|
| year = 2020,
|
| journal = {GitHub repository},
|
| publisher = {GitHub},
|
| howpublished = {\url{https://github.com/huggingface/trl}}
|
| }
|
| ``` |
