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transformer = FluxTransformer2DModel.from_pretrained(
"xiaozaa/catvton-flux-beta",
torch_dtype=torch.bfloat16
)
pipe = FluxFillPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev",
transformer=transformer,
torch_dtype=torch.bfloat16
).to("cuda")@misc{chong2024catvtonconcatenationneedvirtual,
title={CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models},
author={Zheng Chong and Xiao Dong and Haoxiang Li and Shiyue Zhang and Wenqing Zhang and Xujie Zhang and Hanqing Zhao and Xiaodan Liang},
year={2024},
eprint={2407.15886},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2407.15886},
}
@article{lhhuang2024iclora,
title={In-Context LoRA for Diffusion Transformers},
author={Huang, Lianghua and Wang, Wei and Wu, Zhi-Fan and Shi, Yupeng and Dou, Huanzhang and Liang, Chen and Feng, Yutong and Liu, Yu and Zhou, Jingren},
journal={arXiv preprint arxiv:2410.23775},
year={2024}
}