On Distillation of Guided Diffusion Models
Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans
Abstract
Text-guided generation (2 steps) Text-guided generation (4 steps) Image to image translation (3 steps) Class-conditional generation (1 step) Image inpainting (2 steps) Input Input Mask Result 1 Result 2 Output (different styles) Text-guided generation (1 step) Figure 1 . Distilled Stable Diffusion samples generated by our method. Our two-stage distillation approach is able to generate realistic images using only 1 to 4 denoising steps on various tasks. Compared to standard classifier-free guided diffusion models, we reduce the total number of sampling steps by at least 20⇥.
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Install the CLIlune papers fulltext 64df35c4-24c2-434e-9d91-88f9df035551Cited by top-tier papers358
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