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A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom , as a result of advances in deep neural networks .
The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. [1] [2] It is composed of 22 smaller datasets, including 14 new ones. [1]
Open the HTML file in a text editor and copy the HTML source code to the clipboard. Paste the HTML source into the large text box labeled "HTML markup:" on the html to wiki page. Click the blue Convert button at the bottom of the page. Select the text in the "Wiki markup:" text box and copy it to the clipboard. Paste the text to a Wikipedia ...
Full verb conjugation in all tenses, and number conversion from digits to text in the available languages (e.g. "123" → "one hundred twenty-three"), are available through the program interface, as well as free access to online examples of language in use, and a discussion forum moderated by linguists and lexicographers.
[citation needed] The whole basis of language generation is through the training of computer models and algorithms which can learn from a large dataset of information. For example, there are mixed sentence models which tend to perform better as they take a larger sampling size of sentenced data rather than just words [10]. These models ...
Natural language generation (NLG) is a software process that produces natural language output. A widely-cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic ...
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