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  2. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    GPT-3 has 175 billion parameters, each with 16-bit precision, requiring 350GB of storage since each parameter occupies 2 bytes. It has a context window size of 2048 tokens , and has demonstrated strong " zero-shot " and " few-shot " learning abilities on many tasks.

  3. Generative pre-trained transformer - Wikipedia

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

    This was developed by fine-tuning a 12B parameter version of GPT-3 (different from previous GPT-3 models) using code from GitHub. [ 31 ] In March 2022, OpenAI published two versions of GPT-3 that were fine-tuned for instruction-following (instruction-tuned), named davinci-instruct-beta (175B) and text-davinci-001 , [ 32 ] and then started beta ...

  4. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    For example, the small (i.e. 117M parameter sized) GPT-2 model has had twelve attention heads and a context window of only 1k tokens. [44] In its medium version it has 345M parameters and contains 24 layers, each with 12 attention heads. For the training with gradient descent a batch size of 512 was utilized. [28]

  5. The next biggest model out there, as far as we're aware, is OpenAI's GPT-3, which uses a measly 175 billion parameters. Background: Language models are capable of performing a variety of functions ...

  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. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    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] GPT-2 was created as a "direct scale-up" of GPT-1 [6] with a ten-fold increase in both its parameter count and the size of its training dataset. [5]

  8. OpenAI - Wikipedia

    en.wikipedia.org/wiki/OpenAI

    First described in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language model and the successor to GPT-2. [ 182 ] [ 183 ] [ 184 ] OpenAI stated that the full version of GPT-3 contained 175 billion parameters , [ 184 ] two orders of magnitude larger than the 1.5 billion [ 185 ] in the full version of ...

  9. How will GPT-3 change our lives? - AOL

    www.aol.com/gpt-3-change-lives-150036402.html

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