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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.
Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.
Ideogram is a freemium text-to-image model developed by Ideogram, Inc. using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The model is capable of generating legible text in the images compared to other text-to-image models. [1] [2]
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, Generative art, and Synthetic media). They are commonly used for text-to-image generation and neural style transfer. [66]
The copyright disputes mark the beginning of a backlash against a new generation of impressive tools — some of them introduced just last year — that can generate new images, readable text and ...
DALL-E has three components: a discrete VAE, an autoregressive decoder-only Transformer (12 billion parameters) similar to GPT-3, and a CLIP pair of image encoder and text encoder. [22] The discrete VAE can convert an image to a sequence of tokens, and conversely, convert a sequence of tokens back to an image.