SDXL-Lightning:渐进式对抗扩散蒸馏
SDXL-Lightning: Progressive Adversarial Diffusion Distillation
February 21, 2024
作者: Shanchuan Lin, Anran Wang, Xiao Yang
cs.AI
摘要
我们提出了一种扩散蒸馏方法,基于SDXL,在一步/少步1024像素文本到图像生成中取得了新的最先进成果。我们的方法结合了渐进式和对抗性蒸馏,以在质量和模式覆盖之间取得平衡。本文讨论了理论分析、鉴别器设计、模型公式和训练技术。我们以LoRA和完整UNet权重的形式开源了我们蒸馏的SDXL-Lightning模型。
English
We propose a diffusion distillation method that achieves new state-of-the-art
in one-step/few-step 1024px text-to-image generation based on SDXL. Our method
combines progressive and adversarial distillation to achieve a balance between
quality and mode coverage. In this paper, we discuss the theoretical analysis,
discriminator design, model formulation, and training techniques. We
open-source our distilled SDXL-Lightning models both as LoRA and full UNet
weights.