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  2. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    PyTorch is a machine learning library based on the Torch library, [4] [5] [6] ... project was created by Meta and Microsoft in September 2017 for converting models ...

  3. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Microsoft Cognitive Toolkit (CNTK) Microsoft Research: 2016 MIT license [28] Yes ... PyTorch: Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan (Facebook)

  4. DeepSpeed - Wikipedia

    en.wikipedia.org/wiki/DeepSpeed

    The library is designed to reduce computing power and memory use and to train large distributed models with better parallelism on existing computer hardware. [2] [3] DeepSpeed is optimized for low latency, high throughput training.

  5. Open Neural Network Exchange - Wikipedia

    en.wikipedia.org/wiki/Open_Neural_Network_Exchange

    The Open Neural Network Exchange (ONNX) [ˈɒnɪks] [2] is an open-source artificial intelligence ecosystem [3] of technology companies and research organizations that establish open standards for representing machine learning algorithms and software tools to promote innovation and collaboration in the AI sector.

  6. Microsoft Build - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Build

    Microsoft Build (often stylised as //build/) is an annual conference event held by Microsoft, aimed at software engineers and web developers using Windows, Microsoft Azure and other Microsoft technologies.

  7. 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.

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  9. Chainer - Wikipedia

    en.wikipedia.org/wiki/Chainer

    Chainer is an open source deep learning framework written purely in Python on top of NumPy and CuPy Python libraries. The development is led by Japanese venture company Preferred Networks in partnership with IBM, Intel, Microsoft, and Nvidia.