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  2. 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]

  3. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    On August 3, 2022, the company announced the Private Hub, an enterprise version of its public Hugging Face Hub that supports SaaS or on-premises deployment. [ 9 ] In February 2023, the company announced partnership with Amazon Web Services (AWS) which would allow Hugging Face's products available to AWS customers to use them as the building ...

  4. List of large language models - Wikipedia

    en.wikipedia.org/wiki/List_of_large_language_models

    Apache 2.0 Outperforms GPT-3.5 and Llama 2 70B on many benchmarks. [82] Mixture of experts model, with 12.9 billion parameters activated per token. [83] Mixtral 8x22B April 2024: Mistral AI: 141 Unknown Unknown: Apache 2.0 [84] DeepSeek-LLM: November 29, 2023: DeepSeek 67 2T tokens [85]: table 2 12,000: DeepSeek License

  5. List of programming languages for artificial intelligence

    en.wikipedia.org/wiki/List_of_programming...

    Hugging Face's transformers library can manipulate large language models. [4] Jupyter Notebooks can execute cells of Python code, retaining the context between the execution of cells, which usually facilitates interactive data exploration. [5] Elixir is a high-level functional programming language based on the Erlang VM. Its machine-learning ...

  6. 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]

  7. 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.

  8. GPT-J - Wikipedia

    en.wikipedia.org/wiki/GPT-J

    GPT-J or GPT-J-6B is an open-source large language model (LLM) developed by EleutherAI in 2021. [1] As the name suggests, it is a generative pre-trained transformer model designed to produce human-like text that continues from a prompt.

  9. OpenAI o3 - Wikipedia

    en.wikipedia.org/wiki/OpenAI_o3

    On February 2, OpenAI launched OpenAI Deep Research, a ChatGPT service using a version of o3 that makes comprehensive reports within 5 to 30 minutes, based on web searches. [7] On February 6, in response to pressure from rivals like DeepSeek, OpenAI announced an update aimed at enhancing the transparency of the thought process in its o3-mini model.