Showing 4 open source projects for "deep learning with python"

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    Volcano

    Volcano

    A Cloud Native Batch System (Project under CNCF)

    Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms that are commonly required by many classes of batch & elastic workload including machine learning/deep learning, bioinformatics/genomics, and other "big data" applications. These types of applications typically run on generalized domain frameworks like TensorFlow, Spark, Ray, PyTorch, MPI, etc, which Volcano integrates with. Volcano builds upon a decade and a half of experience running a wide variety of high-performance workloads at scale using several systems and platforms, combined with best-of-breed ideas and practices from the open-source community. ...
    Downloads: 32 This Week
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  • 2
    Rainbond

    Rainbond

    A container platform that needs no Kubernetes learning

    Rainbond is an open-source container platform that helps teams build, deploy, upgrade, operate, and deliver applications on Kubernetes without requiring deep Kubernetes expertise. It focuses more on application delivery than low-level cluster resource management. The platform brings source code, container images, templates, dependencies, access management, upgrades, and rollbacks into a standardized graphical workflow. Rainbond is built for complex enterprise delivery scenarios such as...
    Downloads: 15 This Week
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  • 3
    JAX Toolbox

    JAX Toolbox

    Public CI, Docker images for popular JAX libraries

    JAX Toolbox is a development toolkit designed to streamline and optimize the use of JAX for machine learning and high-performance computing on NVIDIA GPUs. It provides prebuilt Docker images, continuous integration pipelines, and optimized example implementations that help developers quickly set up and run JAX workloads without complex configuration. The project supports popular JAX-based frameworks and models, including architectures used for large-scale pretraining such as GPT and LLaMA...
    Downloads: 2 This Week
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  • 4
    KServe

    KServe

    Standardized Serverless ML Inference Platform on Kubernetes

    KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and...
    Downloads: 1 This Week
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