Showing 4 open source projects for "qmmp-plugin-pack"

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  • 1
    ComfyUI-3D-Pack

    ComfyUI-3D-Pack

    An extensive node suite that enables ComfyUI to process 3D inputs

    ComfyUI-3D-Pack is an extension package for the ComfyUI visual AI workflow environment that enables users to generate and manipulate 3D assets using advanced machine learning techniques. ComfyUI itself is a node-based interface for designing and executing generative AI pipelines, and this extension expands its capabilities by introducing nodes specifically designed for working with three-dimensional data.
    Downloads: 11 This Week
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  • 2
    Bootstrap Your Own Latent (BYOL)

    Bootstrap Your Own Latent (BYOL)

    Usable Implementation of "Bootstrap Your Own Latent" self-supervised

    ...There is now new evidence that batch normalization is key to making this technique work well. A new paper has successfully replaced batch norm with group norm + weight standardization, refuting that batch statistics are needed for BYOL to work. Simply plugin your neural network, specifying (1) the image dimensions as well as (2) the name (or index) of the hidden layer, whose output is used as the latent representation used for self-supervised training.
    Downloads: 6 This Week
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  • 3
    Thinc

    Thinc

    A refreshing functional take on deep learning

    Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy. We wrote the new version to let users compose,...
    Downloads: 79 This Week
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  • 4
    AWS Neuron

    AWS Neuron

    Powering Amazon custom machine learning chips

    ...Neuron is pre-integrated into popular machine learning frameworks like TensorFlow, MXNet and Pytorch to provide a seamless training-to-inference workflow. It includes a compiler, runtime driver, as well as debug and profiling utilities with a TensorBoard plugin for visualization.
    Downloads: 2 This Week
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