Qwen 2.5 3b R1 Countdown
This model is a fine-tuned version of Qwen/Qwen2.5-3B-Instruct. It has been trained using TRL.
Source du modèle
- Type
- Text model
- Taille du fichier
- Pas encore enregistré
- Modèle de base
- Qwen/Qwen2.5-3B-Instruct
- Version
- vRevision 61778b8
- Mis à jour
- 22 oct. 2026
- Éditeur
- @gregdlg
- Téléchargements
- 17
- Source
- Hugging Face
Description de la source
Model Card for qwen-2.5-3b-r1-countdown
This model is a fine-tuned version of Qwen/Qwen2.5-3B-Instruct. It has been trained using TRL.
Quick start
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="gregdlg/qwen-2.5-3b-r1-countdown", 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: 1.2.0
- Transformers: 4.57.6
- Pytorch: 2.10.0
- Datasets: 4.8.4
- Tokenizers: 0.22.2
Citations
Cite GRPO as:
@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:
@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}
}
Sources
1 source
Sources
1 sourceVérifié 22 oct.
Extraits de sources
3 extraits
Extraits de sources
3 extraits--- base_model: Qwen/Qwen2.5-3B-Instruct library_name: transformers model_name: qwen-2.5-3b-r1-countdown tags: - generated_from_trainer - trl - grpo licence: license --- # Model Card for qwen-2.5-3b-r1-countdown 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="gregdlg/qwen-2.5-3b-r1-countdown", 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](https://huggingface.co/papers/2402.03300). ### Framework versions - TRL: 1.2.0 - Transformers: 4.57.6 - Pytorch: 2.10.0 - Datasets: 4.8.4 - 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} } ```
Source context: 17 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo gregdlg/qwen-2.5-3b-r1-countdown
Source context: 11 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo gregdlg/qwen-2.5-3b-r1-countdown
