初始化项目,由ModelHub XC社区提供模型
Model: Kwai-Keye/Thyme-RL Source: Original Platform
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README.md
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README.md
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---
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license: mit
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datasets:
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- Kwai-Keye/Thyme-SFT
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- Kwai-Keye/Thyme-RL
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language:
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- en
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metrics:
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- accuracy
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base_model:
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- Qwen/Qwen2.5-VL-7B-Instruct
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pipeline_tag: image-text-to-text
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---
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<div align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/685ba798484e3233f5ff6f11/dxBp6TmwqwNuBuJR9gfQC.png" width="40%" alt="Thyme Logo">
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</div>
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<font size=4><div align='center' >
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[[📖 Home Page](https://thyme-vl.github.io/)]
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[[📖 Github Repo](https://github.com/yfzhang114/Thyme)]
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[[📖 Technique Report](https://arxiv.org/abs/2508.11630)]
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[[📊 Thyme SFT Model](https://huggingface.co/Kwai-Keye/Thyme-SFT)]
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[[📊 Thyme RL Model](https://huggingface.co/Kwai-Keye/Thyme-RL)]
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[[📝 SFT Data](https://huggingface.co/datasets/Kwai-Keye/Thyme-SFT)]
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[[📝 RL Data](https://huggingface.co/datasets/Kwai-Keye/Thyme-RL)]
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</div></font>
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## 🔥 News
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* **`2025.08.15`** 🌟 We are excited to introduce **Thyme: Think Beyond Images**. Thyme transcends traditional ``thinking with images'' paradigms by autonomously generating and executing diverse image processing and computational operations through executable code, significantly enhancing performance on high-resolution perception and complex reasoning tasks. Leveraging a novel two-stage training strategy that combines supervised fine-tuning with reinforcement learning and empowered by the innovative GRPO-ATS algorithm, Thyme achieves a sophisticated balance between reasoning exploration and code execution precision.
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<div align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/685ba798484e3233f5ff6f11/c_D7uX3RT1WUANDRB70ZC.png" width="100%" alt="Thyme Logo">
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</div>
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We have provided the usage instructions, training code, and evaluation code in the [GitHub repo](https://github.com/yfzhang114/Thyme).
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## Citation
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If you find Thyme useful in your research or applications, please cite our paper:
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```bibtex
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@article{zhang2025thyme,
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title={Thyme: Think Beyond Images},
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author={Kwai Keye},
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journal={arXiv preprint},
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year={2025}
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}
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```
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