REDAIGC FT Model used to match UNO In-Context Generation
(with improved quality compared to F.1 dev)
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Diffusers 脚本:
https://github.com/bytedance/UNO
Dit-LoRA 权重:
bytedance-research/UNO · Hugging Face
ComfyUI-nodes 组件:
HM-RunningHub/ComfyUI_RH_UNO: This is a UNO ComfyUI plugin
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propose a highly-consistent data synthesis pipeline to tackle this challenge. This pipeline harnesses the intrinsic in-context generation capabilities of diffusion transformers and generates high-consistency multi-subject paired data. Additionally, we introduce UNO, which consists of progressive cross-modal alignment and universal rotary position embedding. It is a multi-image conditioned subject-to-image model iteratively trained from a text-to-image model. Extensive experiments show that our method can achieve high consistency while ensuring controllability in both single-subject and multi-subject driven generation.