Introducing Würstchen: Fast Diffusion for Image Generation
Würstchen is a text-to-image diffusion model that achieves a 42x spatial compression via a two-stage decoder (VQGAN and Diffusion Autoencoder) and a prior model trained in latent space. This drastically reduces compute costs: training on 512x512 images took only 9,000 GPU hours vs. 150,000 for Stable Diffusion 1.4. The article provides usage examples and performance comparisons.
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