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Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing artificial intelligence boom .
AUTOMATIC1111 Stable Diffusion Web UI (SD WebUI, A1111, or Automatic1111 [3]) is an open source generative artificial intelligence program that allows users to generate images from a text prompt. [4] It uses Stable Diffusion as the base model for its image capabilities together with a large set of extensions and features to customize its output.
ComfyUI is an open source, node-based program that allows users to generate images from a series of text prompts.It uses free diffusion models such as Stable Diffusion as the base model for its image capabilities combined with other tools such as ControlNet and LCM Low-rank adaptation with each tool being represented by a node in the program.
An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
An improved flagship model, Flux 1.1 Pro was released on 2 October 2024. [27] [28] Two additional modes were added on 6 November, Ultra which can generate image at four times higher resolution and up to 4 megapixel without affecting generation speed and Raw which can generate hyper-realistic image in the style of candid photography. [29] [30] [31]
Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [88] language model. Smaller generative AI models with up to a few billion parameters can run on smartphones , embedded devices, and personal computers .
The Latent Diffusion Model (LDM) [1] is a diffusion model architecture developed by the CompVis (Computer Vision & Learning) [2] group at LMU Munich. [ 3 ] Introduced in 2015, diffusion models (DMs) are trained with the objective of removing successive applications of noise (commonly Gaussian ) on training images.
Stable Diffusion 3 (2024-03) [66] changed the latent diffusion model from the UNet to a Transformer model, and so it is a DiT. It uses rectified flow. It uses rectified flow. Stable Video 4D (2024-07) [ 67 ] is a latent diffusion model for videos of 3D objects.
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