SDXL-Lightning:漸進式對抗擴散蒸餾
SDXL-Lightning: Progressive Adversarial Diffusion Distillation
February 21, 2024
作者: Shanchuan Lin, Anran Wang, Xiao Yang
cs.AI
摘要
我們提出了一種擴散蒸餾方法,基於SDXL,在一步/幾步 1024px 文本到圖像生成中實現了新的最先進技術。我們的方法結合了漸進式和對抗式蒸餾,以實現質量和模式覆蓋之間的平衡。在本文中,我們討論了理論分析、鑑別器設計、模型公式和訓練技術。我們將我們蒸餾的SDXL-Lightning模型以LoRA和完整的UNet權重的形式開源。
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.