---
license: apache-2.0
---

## Resources
- [arXiv: Paper](https://arxiv.org/abs/)
- [GitHub: Code](https://github.com/tang-bd/fusedit)

## Quick Start
You can use `FuseDiTPipeline` in our codebase to run the model:

```python
import torch
from diffusion.pipelines import FuseDiTPipeline
pipeline = FuseDiTPipeline.from_pretrained("ooutlierr/fuse-dit").to("cuda")
image = pipeline(
    "your prompt",
    width=512,
    height=512,
    num_inference_steps=25,
    guidance_scale=6.0,
    use_cache=True,
)[0][0]
image.save("test.png")
```

## Citation

```bibtex
@misc{li2025sciencet2iaddressingscientificillusions,
  title={Science-T2I: Addressing Scientific Illusions in Image Synthesis}, 
  author={Jialuo Li and Wenhao Chai and Xingyu Fu and Haiyang Xu and Saining Xie},
  year={2025},
  eprint={2504.13129},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2504.13129}, 
}
```