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

    en.wikipedia.org/wiki/List_of_datasets_for...

    List of GitHub repositories of the project: Operator Framework This data is not pre-processed List of GitHub repositories of the project [408] GitHub repositories referenced in artifacthub.io This data is not pre-processed List of GitHub repositories in artifacthub.io: Red Hat Communities of Practice This data is not pre-processed

  3. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    Git-based code repositories, including discussions and pull requests for projects. models, also with Git-based version control; datasets, mainly in text, images, and audio; web applications ("spaces" and "widgets"), intended for small-scale demos of machine learning applications.

  4. Llama (language model) - Wikipedia

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

    On April 17, 2023, TogetherAI launched a project named RedPajama to reproduce and distribute an open source version of the LLaMA dataset. [47] The dataset has approximately 1.2 trillion tokens and is publicly available for download. [48] Llama 2 foundational models were trained on a data set with 2 trillion tokens. This data set was curated to ...

  5. 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]

  6. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  7. GitHub - Wikipedia

    en.wikipedia.org/wiki/Github

    GitHub (/ ˈ ɡ ɪ t h ʌ b /) is a proprietary developer platform that allows developers to create, store, manage, and share their code. It uses Git to provide distributed version control and GitHub itself provides access control, bug tracking, software feature requests, task management, continuous integration, and wikis for every project. [8]

  8. MNIST database - Wikipedia

    en.wikipedia.org/wiki/MNIST_database

    Sample images from MNIST test dataset. The MNIST database (Modified National Institute of Standards and Technology database [1]) is a large database of handwritten digits that is commonly used for training various image processing systems. [2] [3] The database is also widely used for training and testing in the field of machine learning.

  9. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.