stable diffusion

Stable Diffusion generates high-quality images from text using latent diffusion for computational efficiency. Unlike pixel-space diffusion which operates on 786k dimensions latent diffusion works in compressed 16k dimensional space making it 48x faster. Architecture flows: text prompt to CLIP encoder for conditioning to U-Net for iterative denoising in latent space to VAE decoder for final pixels. Generation takes 20-100 denoising steps with guidance scale 7-15 controlling prompt adherence. Customization includes LoRA for efficient style fine-tuning DreamBooth for teaching new concepts like your face and ControlNet for spatial conditioning with pose edges or depth maps. Being open-source Stable Diffusion runs on 8GB consumer GPUs has thousands of community models and enables unlimited generation without API costs. Versions include SD 1.5 most popular SD 2.1 higher quality and SDXL for 1024px images. Applications span digital art product design marketing gaming and scientific visualization. Stable Diffusion democratized AI image generation through open-source efficiency and customizability.