This model is a fine-tuned version of
Qwen/Qwen2.5-Math-1.5B-Instruct.
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="None", device="cuda")
5output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
6print(output["generated_text"])
This model was trained with BidirectionalPRM, a method introduced in
Solving math word problems with process-and outcome-based feedback.
1@article{uesato2022solving,
2 title = {{Solving Math Word Problems With Process- and Outcome-Based Feedback}},
3 author = {Uesato, Jonathan and Kushman, Nate and Kumar, Ramana and Song, Francis and Siegel, Noah and Wang, Lisa and Creswell, Antonia and Irving, Geoffrey and Higgins, Irina},
4 year = 2022,
5 journal = {arXiv preprint arXiv:2211.14275}
6}
1@software{vonwerra2020trl,
2 title = {{TRL: Transformers Reinforcement Learning}},
3 author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
4 license = {Apache-2.0},
5 url = {https://github.com/huggingface/trl},
6 year = {2020}
7}
