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  2. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    GPT-2 can generate thematically-appropriate text for a range of scenarios, even surreal ones like a CNN article about Donald Trump giving a speech praising the anime character Asuka Langley Soryu. Here, the tendency to generate nonsensical and repetitive text with increasing output length (even in the full 1.5B model) can be seen; in the second ...

  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. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process.

  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. Generative model - Wikipedia

    en.wikipedia.org/wiki/Generative_model

    For example, GPT-3, and its precursor GPT-2, [11] are auto-regressive neural language models that contain billions of parameters, BigGAN [12] and VQ-VAE [13] which are used for image generation that can have hundreds of millions of parameters, and Jukebox is a very large generative model for musical audio that contains billions of parameters. [14]

  7. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Example of prompt engineering for text-to-image generation, with Fooocus In 2022, text-to-image models like DALL-E 2 , Stable Diffusion , and Midjourney were released to the public. [ 68 ] These models take text prompts as input and use them to generate AI-generated images .

  8. Natural language generation - Wikipedia

    en.wikipedia.org/wiki/Natural_language_generation

    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 ...

  9. The Pile (dataset) - Wikipedia

    en.wikipedia.org/wiki/The_Pile_(dataset)

    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]