Stable Diffusion: the full architecture — UNet, VAE and CLIP
Stable Diffusion (Rombach et al., 2022) made high-quality text-to-image generation accessible by combining three independently powerful ideas: running diffusion in a compressed latent space (VAE), conditioning on rich text embeddings (CLIP), and using a U-Net for the denoising. Understanding how these three components fit together is the key to understanding why SD works — and how to control it.
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