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README
Quick start
python
from transformers import pipelinequestion = "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="None", 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 GRPO, a method introduced in DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
Framework versions
- TRL: 1.5.1
- Transformers: 5.9.0
- Pytorch: 2.8.0+cu128
- Datasets: 4.8.5
- Tokenizers: 0.22.2
Citations
Cite GRPO as:
bibtex
@article{shao2024deepseekmath,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
@software{vonwerra2020trl,title = {{TRL: Transformers Reinforcement Learning}},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},license = {Apache-2.0},url = {https://github.com/huggingface/trl},year = {2020}}
Model provider
sengBJY
Model tree
Base
Qwen/Qwen3-4B-Thinking-2507
Fine-tuned
this model
Modalities
Input
Text
Output
Text
Pricing
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Model APIs
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