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Trilogix1/Hugston-yarin-shakedQwen3-Codeforces-GRPO
Hugston-yarin-shakedQwen3-Codeforces-GRPO is a machine learning model from Trilogix1. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Model finetune origin: https://huggingface.co/yarin-shaked/Qwen3-Codeforces-GRPO
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From the Hugging Face model README
Model finetune origin: https://huggingface.co/yarin-shaked/Qwen3-Codeforces-GRPO
Model Card for Hugston-Qwen3-Codeforces-GRPO This model is a fine-tuned version of Qwen/Qwen3-0.6B on the open-r1/codeforces dataset. It has been trained using TRL.
You can use the model with HugstonOne Enterprise Edition

-Note: if the mmproj is inside the same folder with other models non multimodal, the non model will not load unless the mmproj is moved from folder.
Training procedure Visualize in Weights & Biases
This model was trained with GRPO, a method introduced in DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
Framework versions TRL: 0.18.0 Transformers: 4.52.3 Pytorch: 2.6.0 Datasets: 4.2.0 Tokenizers: 0.21.4 Citations Cite GRPO as:
@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:
@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}} }