Showing 2 open source projects for "extreme learning machine"

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  • 1
    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 variants. ...
    Downloads: 4 This Week
    Last Update:
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  • 2
    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 Canary Rollouts to your ML deployments. ...
    Downloads: 4 This Week
    Last Update:
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