Showing 5 open source projects for "python sample"

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    Netron

    Netron

    Visualizer for neural network, deep learning, machine learning models

    ...Netron has experimental support for TensorFlow, PyTorch, TorchScript, OpenVINO, Torch, Arm NN, BigDL, Chainer, CNTK, Deeplearning4j, MediaPipe, ML.NET, scikit-learn, TensorFlow.js. There is an extense variety of sample model files to download or open using the browser version. It is supported by macOS, Windows, Linux, Python Server and browser.
    Downloads: 56 This Week
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  • 2
    Opacus

    Opacus

    Training PyTorch models with differential privacy

    Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance, and allows the client to online track the privacy budget expended at any given moment. Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source,...
    Downloads: 0 This Week
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  • 3
    Tiny CUDA Neural Networks

    Tiny CUDA Neural Networks

    Lightning fast C++/CUDA neural network framework

    ...These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding.
    Downloads: 0 This Week
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  • 4
    I3D models trained on Kinetics

    I3D models trained on Kinetics

    Convolutional neural network model for video classification

    Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with...
    Downloads: 0 This Week
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  • 5
    Compare GAN

    Compare GAN

    Compare GAN code

    compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. With...
    Downloads: 0 This Week
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