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  2. OpenVINO - Wikipedia

    en.wikipedia.org/wiki/OpenVINO

    OpenVINO is an open-source software toolkit for optimizing and deploying deep learning models. It enables programmers to develop scalable and efficient AI solutions with relatively few lines of code. It supports several popular model formats [2] and categories, such as large language models, computer vision, and generative AI.

  3. Weka (software) - Wikipedia

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

    KNIME is a machine learning and data mining software implemented in Java. Massive Online Analysis (MOA) is an open-source project for large scale mining of data streams, also developed at the University of Waikato in New Zealand. Neural Designer is a data mining software based on deep learning techniques written in C++.

  4. Caffe (software) - Wikipedia

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

    Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, originally developed at University of California, Berkeley. It is open source, under a BSD license. [4] It is written in C++, with a Python interface. [5]

  5. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    The Transformers library is a Python package that contains open-source implementations of transformer models for text, image, and audio tasks. It is compatible with the PyTorch, TensorFlow and JAX deep learning libraries and includes implementations of notable models like BERT and GPT-2. [16]

  6. SqueezeNet - Wikipedia

    en.wikipedia.org/wiki/SqueezeNet

    This original version of SqueezeNet was implemented on top of the Caffe deep learning software framework. Shortly thereafter, the open-source research community ported SqueezeNet to a number of other deep learning frameworks. On February 26, 2016, Eddie Bell released a port of SqueezeNet for the Chainer deep learning framework. [3]

  7. Deeplearning4j - Wikipedia

    en.wikipedia.org/wiki/Deeplearning4j

    Deeplearning4j is open-source software released under Apache License 2.0, [6] developed mainly by a machine learning group headquartered in San Francisco. [7] It is supported commercially by the startup Skymind, which bundles DL4J, TensorFlow , Keras and other deep learning libraries in an enterprise distribution called the Skymind Intelligence ...

  8. DeepSpeed - Wikipedia

    en.wikipedia.org/wiki/DeepSpeed

    Features include mixed precision training, single-GPU, multi-GPU, and multi-node training as well as custom model parallelism. The DeepSpeed source code is licensed under MIT License and available on GitHub. [5] The team claimed to achieve up to a 6.2x throughput improvement, 2.8x faster convergence, and 4.6x less communication. [6]

  9. Neuroevolution - Wikipedia

    en.wikipedia.org/wiki/Neuroevolution

    mature open source neuroevolution project implemented in C#/.Net. ANNEvolve is an Open Source AI Research Project (Downloadable source code in C and Python with a tutorial & miscellaneous writings and illustrations "Nils T Siebel – EANT2 – Evolutionary Reinforcement Learning of Neural Networks". siebel-research.de