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  2. Microsoft Copilot - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Copilot

    Copilot utilizes the Microsoft Prometheus model. According to Microsoft, this uses a component called the Orchestrator, which iteratively generates search queries, to combine the Bing search index and results [86] with OpenAI's GPT-4, [87] [88] GPT-4 Turbo, [89] and GPT-4o [90] foundational large language models, which have been fine-tuned ...

  3. llama.cpp - Wikipedia

    en.wikipedia.org/wiki/Llama.cpp

    The GGUF (GGML Universal File) [26] file format is a binary format that stores both tensors and metadata in a single file, and is designed for fast saving, and loading of model data. [27] It was introduced in August 2023 by the llama.cpp project to better maintain backwards compatibility as support was added for other model architectures.

  4. Llama (language model) - Wikipedia

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

    The model architecture remains largely unchanged from that of LLaMA-1 models, but 40% more data was used to train the foundational models. [26] The accompanying preprint [26] also mentions a model with 34B parameters that might be released in the future upon satisfying safety targets. LLaMa 2 includes foundation models and models fine-tuned for ...

  5. 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. The largest and most capable LLMs are generative pretrained transformers (GPTs).

  6. 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.

  7. BERT (language model) - Wikipedia

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

    It uses the encoder-only transformer architecture. It is notable for its dramatic improvement over previous state-of-the-art models, and as an early example of a large language model . As of 2020 [update] , BERT is a ubiquitous baseline in natural language processing (NLP) experiments.

  8. LangChain - Wikipedia

    en.wikipedia.org/wiki/LangChain

    LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.

  9. 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 ]