Stable Diffusion

Latent diffusion models (LDMs) are a type of image generation technique that work by iteratively "de-noising" data in a latent representation space, and then decoding the representation into a full image. This is in contrast to other popular image synthesis methods such as generative adversarial networks (GANs) and the auto-regressive technique used by DALL-E. The Stable Diffusion model is created by a collaboration between engineers and researchers from CompVis, Stability AI, and LAION and released under a Creative ML OpenRAIL-M license, wich means that it can be used for commercial and non-commercial purposes. The release of this file is the culmination of many hours of collective effort to compress the visual information of humanity into a few gigabytes. Furthermore, the model also supports image-to-image style transfer, as well as upscaling and generating an images from a simple sketch. Included is also an AI-based Safty Classifier, which understands concepts and other factors in generations to remove outputs that may not be desired by the model user.

General
Relese date	August 22, 2022
Research Paper	https://ommer-lab.com/research/latent-diffusion-models/
Type	Deep learning text to image model

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Stable diffusion Tutorials

Knowledge Base

Find out how it is working!

• Research Paper The Stable Diffusion paper describes the model and its training process in detail.
• Stable Diffusion Demo You can play around with Stable Diffusion on Hugging Face
• GitHub Repository Visit the Stable Diffusion v2 repository on GitHub
• dreamstudio Online stable diffusion interface with a lot of optional configurations

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Boilerplates

Get started with technology!

• Stable Diffusion Colab A Colab notebook that shows how to use Stable Diffusion with GPU!
• Stable Diffusion & Whisper Colab A Colab notebook that shows how to use Stable Diffusion with Whisper!
• Stable Diffusion Interpolation V2.2 A Colab notebook about Stable Diffusion Interpolation!