metadata
license: apache-2.0
Resources
Quick Start
You can use FuseDiTPipeline in our codebase to run the model:
import torch
from diffusion.pipelines import FuseDiTPipeline
pipeline = FuseDiTPipeline.from_pretrained("ooutlierr/fusedit").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
@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},
}