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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.
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.
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.
This template allows posts from social media sites other than (but inclusive of) Twitter, to be easily quoted within articles. This is an alternative to (and fork of) Template:Tweet. It is more appropriate to use this template than a screenshot of a tweet or post, because the text it contains will be accessible to screen readers.
The film Twitter take generator parrots a certain kind of internet discourse where director's names are buzzwords and debates about the Marvel Cinematic Universe are seemingly always trending. If ...
NovelAI is an online cloud-based, SaaS model, and a paid subscription service for AI-assisted storywriting [2] [3] [4] and text-to-image synthesis, [5] originally launched in beta on June 15, 2021, [6] with the image generation feature being implemented later on October 3, 2022.
The tweet spiraled into a meme, and Twitter users started to post their own takes on the ideal male body. this is the ideal male body. you may not like it, but this is what peak performance looks ...
For text-to-image models, textual inversion [55] performs an optimization process to create a new word embedding based on a set of example images. This embedding vector acts as a "pseudo-word" which can be included in a prompt to express the content or style of the examples.