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Model Server for Apache MXNet is a tool for serving neural net models for inference

Project description

Apache MXNet Model Server (MMS) is a flexible and easy to use tool for serving deep learning models exported from MXNet or the Open Neural Network Exchange (ONNX).

Use the MMS Server CLI, or the pre-configured Docker images, to start a service that sets up HTTP endpoints to handle model inference requests.

Detailed documentation and examples are provided in the docs folder.

Prerequisites

If you wish to use ONNX with MMS, you will need to first install a protobuf compiler. This is not needed if you wish to serve MXNet models.

Instructions for installing MMS with ONNX.

Installation

pip install mxnet-model-server

Development

We welcome new contributors of all experience levels. For information on how to install MMS for development, refer to the MMS docs.

Source code

You can check the latest source code as follows:

git clone https://github.com/awslabs/mxnet-model-server.git

Testing

After installation, try out the MMS Quickstart for Serving a Model and Exporting a Model.

Help and Support

Citation

If you use MMS in a publication or project, please cite MMS: https://github.com/awslabs/mxnet-model-server

Project details


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Filename, size & hash SHA256 hash help File type Python version Upload date
mxnet_model_server-0.4-py2.py3-none-any.whl (13.4 MB) Copy SHA256 hash SHA256 Wheel py2.py3 May 25, 2018

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