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  2. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    Generative Pre-trained Transformer 2 (GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages. [2] It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019. [3] [4] [5]

  3. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  4. OpenAI - Wikipedia

    en.wikipedia.org/wiki/OpenAI

    OpenAI also makes GPT-4 available to a select group of applicants through their GPT-4 API waitlist; [239] after being accepted, an additional fee of US$0.03 per 1000 tokens in the initial text provided to the model ("prompt"), and US$0.06 per 1000 tokens that the model generates ("completion"), is charged for access to the version of the model ...

  5. GPT2 - Wikipedia

    en.wikipedia.org/wiki/GPT2

    GPT-2, a text generating model developed by OpenAI Topics referred to by the same term This disambiguation page lists articles associated with the same title formed as a letter–number combination.

  6. OpenAI o1 - Wikipedia

    en.wikipedia.org/wiki/OpenAI_o1

    OpenAI o1 is a generative pre-trained transformer (GPT). A preview of o1 was released by OpenAI on September 12, 2024. o1 spends time "thinking" before it answers, making it better at complex reasoning tasks, science and programming than GPT-4o. [1] The full version was released on December 5, 2024. [2]

  7. Category:Generative pre-trained transformers - Wikipedia

    en.wikipedia.org/wiki/Category:Generative_pre...

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Pages for logged out editors learn more

  8. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    The number of neurons in the middle layer is called intermediate size (GPT), [55] filter size (BERT), [35] or feedforward size (BERT). [35] It is typically larger than the embedding size. For example, in both GPT-2 series and BERT series, the intermediate size of a model is 4 times its embedding size: =.

  9. File:Full GPT architecture.svg - Wikipedia

    en.wikipedia.org/wiki/File:Full_GPT_architecture.svg

    Original file (SVG file, nominally 500 × 600 pixels, file size: 19 KB) This is a file from the Wikimedia Commons . Information from its description page there is shown below.