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  2. GPT-1 - Wikipedia

    en.wikipedia.org/wiki/GPT-1

    The GPT-1 architecture was a twelve-layer decoder-only transformer, using twelve masked self-attention heads, with 64-dimensional states each (for a total of 768). Rather than simple stochastic gradient descent , the Adam optimization algorithm was used; the learning rate was increased linearly from zero over the first 2,000 updates to a ...

  3. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, [ 3 ] providing relevant context, or describing a character for the AI to mimic.

  4. List of free and open-source software packages - Wikipedia

    en.wikipedia.org/wiki/List_of_free_and_open...

    This is a list of free and open-source software (FOSS) packages, computer software licensed under free software licenses and open-source licenses. Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. [1]

  5. 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.

  6. Llama (language model) - Wikipedia

    en.wikipedia.org/wiki/Llama_(language_model)

    The average dialog depth was 3.9 in the Meta examples, 3.0 for Anthropic Helpful and Anthropic Harmless sets, and 1.0 for five other sets, including OpenAI Summarize, StackExchange, etc. Llama 3 consists of mainly English data, with over 5% in over 30 other languages.

  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 o1 - Wikipedia

    en.wikipedia.org/wiki/OpenAI_o1

    OpenAI o1 is a reflective 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 to ChatGPT users on December 5, 2024. [2]

  9. AutoGPT - Wikipedia

    en.wikipedia.org/wiki/AutoGPT

    AutoGPT is an open-source "AI agent" that, given a goal in natural language, will attempt to achieve it by breaking it into sub-tasks and using the Internet and other tools in an automatic loop. [1] It uses OpenAI's GPT-4 or GPT-3.5 APIs, [2] and is among the first examples of an application using GPT-4 to perform autonomous tasks. [3]