stable-diffusion

A latent text-to-image diffusion model

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CompVis

CompVis • individual

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Created

Aug 10, 2022

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README Summary

Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. It operates in the latent space of powerful pretrained autoencoders, making it computationally efficient while maintaining high quality output. The model enables applications like text-to-image generation, image inpainting, and image-to-image translation.

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Latent Diffusion ModelsText-to-Image GenerationDiffusion Model TrainingComputer VisionDeep LearningGenerative AIImage SynthesisCLIP Text EncodingU-Net ArchitectureVariational Autoencoders

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Latent Diffusion ModelsText-to-Image GenerationDiffusion Model TrainingComputer VisionDeep LearningGenerative AIImage SynthesisCLIP Text EncodingU-Net ArchitectureVariational AutoencodersGenerative Adversarial NetworksMultimodalProbabilistic Machine LearningOn-premiseConcept Art DevelopmentNeural Network Architecture DesignTextMarketingSelf-hostedCloud APIPrototype Design MockupsCreative IndustriesOpen Source AIContent Generation for MarketingMultimodal AIE-commerceFoundation ModelsGamingCreative Writing IllustrationEntertainmentArtistic Image CreationImageContrastive LearningDigital ArtProduct VisualizationJupyter Notebook

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Updated 1 years ago

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Quality: medium
Maturity: research

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Jupyter Notebook100.0%

Timeline

Project created: Aug 10, 2022
Forked: Mar 12, 2026
Your last push: 1 years ago
Upstream last push: 1 years ago
Tracked since: Jun 18, 2024

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