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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.
Riffusion is a neural network, designed by Seth Forsgren and Hayk Martiros, that generates music using images of sound rather than audio. [1] It was created as a fine-tuning of Stable Diffusion , an existing open-source model for generating images from text prompts, on spectrograms . [ 1 ]
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.
Stable Diffusion, prompt a photograph of an astronaut riding a horse Producing high-quality visual art is a prominent application of generative AI. [ 65 ] Generative AI systems trained on sets of images with text captions include Imagen , DALL-E , Midjourney , Adobe Firefly , FLUX.1 , Stable Diffusion and others (see Artificial intelligence art ...
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 .
The model was made available on December 15, 2022, with the code also freely available on GitHub. [42] It is one of many models derived from Stable Diffusion. [44] Riffusion is classified within a subset of AI text-to-music generators. In December 2022, Mubert [46] similarly used Stable Diffusion to turn descriptive text into music loops. In ...
Stability AI offered computational resources to support the project, and the model was officially released in August 2022 under the name Stable Diffusion. [20] Rombach, Blattmann, Esser and Lorenz subsequently joined Stability AI, leading the development of subsequent Stable Diffusion models. [ 21 ]
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.