Showing 4 open source projects for "registry"

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    AWS Deep Learning Containers

    AWS Deep Learning Containers

    A set of Docker images for training and serving models in TensorFlow

    ...Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. This project is licensed under the Apache-2.0 License. Ensure you have access to an AWS account i.e. setup your environment such that awscli can access your account via either an IAM user or an IAM role.
    Downloads: 1 This Week
    Last Update:
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  • 2
    OpenFold

    OpenFold

    Trainable, memory-efficient, and GPU-friendly PyTorch reproduction

    ...We've publicly released model weights and our training data — some 400,000 MSAs and PDB70 template hit files — under a permissive license. Model weights are available via scripts in this repository while the MSAs are hosted by the Registry of Open Data on AWS (RODA).
    Downloads: 0 This Week
    Last Update:
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  • 3
    Prem AI

    Prem AI

    Prem provides a unified environment to develop AI applications

    ...For example, all models of type Chat expose the OpenAI API for easy of integration of existing tools and AI app ecosystem. Each service we support it's published on the Prem Registry.
    Downloads: 46 This Week
    Last Update:
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  • 4
    SageMaker MXNet Inference Toolkit

    SageMaker MXNet Inference Toolkit

    Toolkit for allowing inference and serving with MXNet in SageMaker

    ...Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well.
    Downloads: 0 This Week
    Last Update:
    See Project
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