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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.
Ideogram was founded in 2022 by Mohammad Norouzi, William Chan, Chitwan Saharia, and Jonathan Ho to develop a better text-to-image model. [3]It was first released with its 0.1 model on August 22, 2023, [4] after receiving $16.5 million in seed funding, which itself was led by Andreessen Horowitz and Index Ventures.
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.
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If your copyright-free image is already available online and you have documented permission or a license from the image owner to use it, you can often copy the image's URL by right-clicking on the image in your web browser (or using Control + click on a Mac) and choosing Copy image address or Copy image location.
[a] Using thumb generates a thumbnail picture, typically sized differently from the original image. For guidance on the caption text to associate with images, see Wikipedia:Manual of Style/Captions. Several options can affect a thumbnail's placement and size, described below. The next two subsections describe adding images to text wrapping ...
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