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  2. Wikipedia:Large language models and copyright - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Large_language...

    Apart from the a possibility that saving an LLM output may cause verbatim non-free content to be carried over to the article, these models can produce derivative works. For example, an LLM can rephrase a copyrighted text using fewer, the same, or more words than the original – editors should mind the distinction between a summary and an ...

  3. 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.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.

  4. BLOOM (language model) - Wikipedia

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

    BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [3]

  5. Llama (language model) - Wikipedia

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

    Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of large language models (LLMs) released by Meta AI starting in February 2023. [2] [3] The latest version is Llama 3.3, released in December 2024.

  6. Wikipedia:List of free online resources - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:List_of_free...

    The following list is meant to help you with your own research, by offering links to respectable information sources on the web, available free of charge.Inclusion on the list doesn't automatically mean the absolute truth is on these websites, so always be critical and compare information between different sources.

  7. llama.cpp - Wikipedia

    en.wikipedia.org/wiki/Llama.cpp

    llama.cpp began development in March 2023 by Georgi Gerganov as an implementation of the Llama inference code in pure C/C++ with no dependencies. This improved performance on computers without GPU or other dedicated hardware, which was a goal of the project.

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