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

4. 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]

5. Weblate - Wikipedia

   en.wikipedia.org/wiki/Weblate

   Weblate is an open source web-based translation tool with version control. It includes several hundred languages with basic definitions, and enables the addition of more language definitions, all definitions can be edited by the web community or a defined set of people, as well as through integrating machine translation, such as DeepL Translator, Amazon Translate, or Google Translate.

6. OmegaT - Wikipedia

   en.wikipedia.org/wiki/OmegaT

   OmegaT is a computer-assisted translation tool written in the Java programming language. It is free software originally developed by Keith Godfrey in 2000, and is currently developed by a team led by Aaron Madlon-Kay. OmegaT is intended for professional translators.

7. 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.