--- base_model: Qwen/Qwen2.5-3B-Instruct datasets: lhkhiem28/HA-GRPO-datasets library_name: transformers model_name: Qwen2.5-3B-ha_grpo tags: - generated_from_trainer - open-r1 - trl - ha_grpo licence: license --- # Model Card for Qwen2.5-3B-ha_grpo This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) on the [lhkhiem28/HA-GRPO-datasets](https://huggingface.co/datasets/lhkhiem28/HA-GRPO-datasets) dataset. 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="lhkhiem28/Qwen2.5-3B-ha_grpo", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [ ](https://wandb.ai/kle3/huggingface/runs/9a582f7n) This model was trained with HA_GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300). ### Framework versions - TRL: 0.18.0.dev0 - Transformers: 4.52.0 - Pytorch: 2.6.0 - Datasets: 4.8.4 - Tokenizers: 0.21.4 ## Citations Cite HA_GRPO as: ```bibtex @article{zhihong2024deepseekmath, title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}}, author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo}, year = 2024, eprint = {arXiv:2402.03300}, } ``` 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}} } ```
