README.md

---
license: mit
datasets:
- Kwai-Keye/Thyme-SFT
- Kwai-Keye/Thyme-RL
language:
- en
metrics:
- accuracy
base_model:
- Qwen/Qwen2.5-VL-7B-Instruct
pipeline_tag: image-text-to-text
---
<div align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/685ba798484e3233f5ff6f11/dxBp6TmwqwNuBuJR9gfQC.png" width="40%" alt="Thyme Logo">
</div>

<font size=4><div align='center' >  
[[📖 Home Page](https://thyme-vl.github.io/)] 
[[📖 Github Repo](https://github.com/yfzhang114/Thyme)] 
[[📖 Technique Report](https://arxiv.org/abs/2508.11630)] 

[[📊 Thyme SFT Model](https://huggingface.co/Kwai-Keye/Thyme-SFT)] 
[[📊 Thyme RL Model](https://huggingface.co/Kwai-Keye/Thyme-RL)] 
[[📝 SFT Data](https://huggingface.co/datasets/Kwai-Keye/Thyme-SFT)] 
[[📝 RL Data](https://huggingface.co/datasets/Kwai-Keye/Thyme-RL)] 
</div></font>

## 🔥 News
* **`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.

<div align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/685ba798484e3233f5ff6f11/c_D7uX3RT1WUANDRB70ZC.png" width="100%" alt="Thyme Logo">
</div>

We have provided the usage instructions, training code, and evaluation code in the [GitHub repo](https://github.com/yfzhang114/Thyme).

## Citation

If you find Thyme useful in your research or applications, please cite our paper:

```bibtex
@article{zhang2025thyme,
  title={Thyme: Think Beyond Images},
  author={Kwai Keye},
  journal={arXiv preprint},
  year={2025}
}
```