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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]
It is based on the transformer deep learning architecture, pre-trained on large data sets of unlabeled text, and able to generate novel human-like content. [2] [3] As of 2023, most LLMs had these characteristics [7] and are sometimes referred to broadly as GPTs. [8] The first GPT was introduced in 2018 by OpenAI. [9]
There is free software on the market capable of recognizing text generated by generative artificial intelligence (such as GPTZero), as well as images, audio or video coming from it. [99] Potential mitigation strategies for detecting generative AI content include digital watermarking , content authentication , information retrieval , and machine ...
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.
An instance of GPT-2 writing a paragraph based on a prompt from its own Wikipedia article in February 2021. Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language model and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative versions ...
Sora is a text-to-video model developed by OpenAI. The model generates short video clips based on user prompts, and can also extend existing short videos. Sora was released publicly for ChatGPT Plus and ChatGPT Pro users in December 2024. [1] [2]
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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: =.
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