This model is a fine-tuned version of
Qwen/Qwen2.5-7B on the
DigitalLearningGmbH/MATH-lighteval dataset.
It has been trained using
TRL.
1from transformers import pipeline
2
3question = "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?"
4generator = pipeline("text-generation", model="chenggong1995/Qwen-2.5-Base-7B-Max-v1", device="cuda")
5output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
6print(output["generated_text"])
1@article{zhihong2024deepseekmath,
2 title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
3 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},
4 year = 2024,
5 eprint = {arXiv:2402.03300},
6}
7
1@misc{vonwerra2022trl,
2 title = {{TRL: Transformer Reinforcement Learning}},
3 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},
4 year = 2020,
5 journal = {GitHub repository},
6 publisher = {GitHub},
7 howpublished = {\url{https://github.com/huggingface/trl}}
8}
