Trilogix1/Hugston-yarin-shakedQwen3-Codeforces-GRPO

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.

This model was converted and Quantized by Hugston Team.

You can use the model with HugstonOne Enterprise Edition

Tested.

Watch HugstonOne coding and preview in action: https://vimeo.com/1121493834?share=copy&fl=sv&fe=ci Usage -Download App HugstonOne at Hugston.com or at https://github.com/Mainframework -Download model from https://hugston.com/explore?folder=llm_models or Huggingface -If you already have the Llm Model downloaded chose it by clicking pick model in HugstonOne -Then click Load model in Cli or Server

-For multimodal use you need a VL/multimodal LLM model with the Mmproj file in the same folder. -Select model and select mmproj.

-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.

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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}} }