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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.
It has Arabic to English translations and English to Arabic, as well as a significant quantity of technical terminology. It is useful to translators as its search results are given in context. [ 6 ] Almaany offers correspondent meanings for Arabic terms with semantically similar words and is widely used in Arabic language research. [ 7 ]
As of August 2023, more than 15 billion images had been generated using text-to-image algorithms, with 80% of these created by models based on Stable Diffusion. [184] If AI-generated content is included in new data crawls from the Internet for additional training of AI models, defects in the resulting models may occur. [185]
It consists of two subcorpora; one contains the English originals and the other their Arabic translations. As for the English subcorpus, it contains 3,794,677 word tokens, with 78,606 word types. The Arabic subcorpus has a slightly fewer word tokens (3,755,741), yet differs greatly in terms of the number of word types, which is 143,727.
The following English words have been acquired either directly from Arabic or else indirectly by passing from Arabic into other languages and then into English. Most entered one or more of the Romance languages before entering English. To qualify for this list, a word must be reported in etymology dictionaries as having descended from Arabic.
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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.
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