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2. Text-to-image model - Wikipedia

   en.wikipedia.org/wiki/Text-to-image_model

   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.

3. DALL-E - Wikipedia

   en.wikipedia.org/wiki/DALL-E

   DALL-E, DALL-E 2, and DALL-E 3 (stylised DALL·E, and pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.

4. Text-to-image personalization - Wikipedia

   en.wikipedia.org/wiki/Text-to-image_personalization

   Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models. In this task, a generative model that was trained on large-scale data (usually a foundation model ), is adapted such that it can generate images of novel, user-provided concepts.

5. Generative artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Generative_artificial...

   Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs, [112] if trained on a racially biased data set. A number of methods for mitigating bias have been attempted, such as altering input prompts [113] and reweighting training data. [114]

6. Ideogram (text-to-image model) - Wikipedia

   en.wikipedia.org/wiki/Ideogram_(text-to-image_model)

   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]

7. Flux (text-to-image model) - Wikipedia

   en.wikipedia.org/wiki/Flux_(text-to-image_model)

   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 was founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.