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

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

    3.4 TB English text, 1.4 TB Chinese text, 1.1 TB Russian text, 595 MB German text, 431 MB French text, and data for 150+ languages (figures for version 23.01) JSON Lines [458] Natural Language Processing, Text Prediction 2021 [459] [460] Ortiz Suarez, Abadji, Sagot et al. OpenWebText An open-source recreation of the WebText corpus.

  3. Torch (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Torch_(machine_learning)

    Torch development moved in 2017 to PyTorch, a port of the library to Python. [4] [5] [6] ... Simpler modules like Linear, Tanh and Max make up the basic component ...

  4. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...

  5. JAX (software) - Wikipedia

    en.wikipedia.org/wiki/Google_JAX

    JAX is a machine learning framework for transforming numerical functions developed by Google with some contributions from Nvidia. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).

  6. PyTorch Lightning - Wikipedia

    en.wikipedia.org/wiki/PyTorch_Lightning

    PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.

  7. Attention (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Attention_(machine_learning)

    5. Pytorch tutorial Both encoder & decoder are needed to calculate attention. [42] Both encoder & decoder are needed to calculate attention. [48] Decoder is not used to calculate attention. With only 1 input into corr, W is an auto-correlation of dot products. w ij = x i x j. [49] Decoder is not used to calculate attention. [50]

  8. Monte Carlo tree search - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_tree_search

    The rating of best Go-playing programs on the KGS server since 2007. Since 2006, all the best programs use Monte Carlo tree search. [14]In 2006, inspired by its predecessors, [15] Rémi Coulom described the application of the Monte Carlo method to game-tree search and coined the name Monte Carlo tree search, [16] L. Kocsis and Cs.

  9. Orders of magnitude (data) - Wikipedia

    en.wikipedia.org/wiki/Orders_of_magnitude_(data)

    size of an AVX2 vector register, present on newer x86-64 CPUs 2 9: 512 bits (64 bytes) – maximum key length for the standard strong cryptographic message digests in 2004 – size of an AVX-512 vector register, present on some x86-64 CPUs 10 3: kilobit (kbit) 1,000 bits (125 bytes) 2 10: kibibit (Kibit) 1,024 bits (128 bytes) - RAM ...