Qwen2.5 VL 7B Instruct 0415 H200 Ng8 Format Gpt Sem

--- base_model: unsloth/qwen2.5-vl-7b-instruct-unsloth-bnb-4bit library_name: transformers model_name: Qwen2.5-VL-7B-Instruct-0415-h200-ng8-format-gpt-sem tags: - generated_from_trainer - unsloth - grpo - trl licence: license --- # Model Card for Qwen2.5-VL-7B-Instruct-0415-h200-ng8-format-gpt-sem This model is a fine-tuned version of [unsloth/qwen2.5-vl-7b-instruct-unsloth-bnb-4bit](https://huggingface.co/unsloth/qwen2.5-vl-7b-instruct-unsloth-bnb-4bit). 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="elffiona/Qwen2.5-VL-7B-Instruct-0415-h200-ng8-format-gpt-sem", 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: 0.22.2 - Transformers: 4.57.0 - Pytorch: 2.10.0 - Datasets: 4.3.0 - 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 @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}} } ```

Source context: 0 downloads · 0 likes · Library transformers · Repo elffiona/Qwen2.5-VL-7B-Instruct-0415-h200-ng8-format-gpt-sem

Source context: 0 downloads · 0 likes · Library transformers · Repo elffiona/Qwen2.5-VL-7B-Instruct-0415-h200-ng8-format-gpt-sem