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  2. List of datasets for machine-learning research - Wikipedia

    https://en.wikipedia.org/wiki/List_of_datasets_for...

    Metatext NLP: https://metatext.io/datasets web repository maintained by community, containing nearly 1000 benchmark datasets, and counting. Provides many tasks from classification to QA, and various languages from English, Portuguese to Arabic.

  3. The Pile (dataset) - Wikipedia

    https://en.wikipedia.org/wiki/The_Pile_(dataset)

    The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. [1] [2] It is composed of 22 smaller datasets, including 14 new ones. [1]

  4. Hugging Face - Wikipedia

    https://en.wikipedia.org/wiki/Hugging_Face

    huggingface.co Hugging Face, Inc. is an American company that develops computation tools for building applications using machine learning . It is known for its transformers library built for natural language processing applications.

  5. BLOOM (language model) - Wikipedia

    https://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]

  6. XLNet - Wikipedia

    https://en.wikipedia.org/wiki/XLNet

    The dataset was composed of BooksCorpus, and English Wikipedia, Giga5, ClueWeb 2012-B, and Common Crawl. It was trained on 512 TPU v3 chips, for 5.5 days. At the end of training, it still under-fitted the data, meaning it could have achieved lower loss with more training.

  7. Llama (language model) - Wikipedia

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

    Code Llama is a fine-tune of LLaMa 2 with code specific datasets. 7B, 13B, and 34B versions were released on August 24, 2023, with the 70B releasing on the January 29, 2024. [29] Starting with the foundation models from LLaMa 2, Meta AI would train an additional 500B tokens of code datasets, before an additional 20B token of long-context data ...

  8. BookCorpus - Wikipedia

    https://en.wikipedia.org/wiki/BookCorpus

    The dataset consists of around 985 million words, and the books that comprise it span a range of genres, including romance, science fiction, and fantasy. [ 3 ] The corpus was introduced in a 2015 paper by researchers from the University of Toronto and MIT titled "Aligning Books and Movies: Towards Story-like Visual Explanations by Watching ...

  9. Foundation model - Wikipedia

    https://en.wikipedia.org/wiki/Foundation_model

    The Stanford Institute for Human-Centered Artificial Intelligence's (HAI) Center for Research on Foundation Models (CRFM) coined the term "foundation model" in August 2021 [16] to mean "any model that is trained on broad data (generally using self-supervision at scale) that can be adapted (e.g., fine-tuned) to a wide range of downstream tasks". [17]