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Stable Diffusion is an open latent diffusion text-to-image model that generates diverse photorealistic and artistic images from textual prompts. It uses diffusion processes in latent space to enable efficient image synthesis for local experiments and production use. Model tuning, safety mitigations, and licensing influence deployment and outputs.
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Stable Diffusion is a generative diffusion model that can create images from text descriptions and other inputs.
Stable Diffusion emerged in 2022 from collaboration between CompVis, Stability AI, and Runway as a publicly accessible text-to-image model. The approach builds on diffusion models and latent image representations.
The model corrupts a compressed image representation with noise and learns to reverse that process step by step. During generation, a text description guides the path from noise toward a matching image.
Image noise is gradually transformed back into a structured representation.
Computation uses a compressed representation of images.
A text description guides the desired image output.
Stable Diffusion enables local or hosted image generation, style variations, and creative prototyping.
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