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Stable Diffusion is a latent diffusion model (LDM) for machine learning that uses probability distributions to generate outputs that are statistically similar to the data the model was trained on. It can be used for inpainting or outpainting elements within an existing image, as well as image-to-image translation. The model was initially trained on human-labeled images scraped from the Internet and was tested at scale before the release with over 10,000 beta testers. The latest version of the foundation model, SDXL 1.0, was released in August 2023 and is said to have been trained with 3.5 billion parameters and thousands of hyperparameters.