Project Description
Model Archiver is a tool used for creating archives of trained neural net models that can be consumed by MXNet-Model-Server inference.
Use the Model Archiver CLI to start create a .mar file.
Model Archiver is part of MMS. However,you ca install Model Archiver stand alone.
Detailed documentation and examples are provided in the README.
Prerequisites
ONNX support is optional in model-archiver tool. It’s not installed by default with model-archiver.
If you wish to package a ONNX model, you will need to first install a protobuf compiler, onnx and mxnet manually.
Installation
pip install model-archiver
Development
We welcome new contributors of all experience levels. For information on how to install MMS for development, refer to the MMS docs.
Important links
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 Create a model archive and Serving 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
Metadata
Release files for model-archiver 1.0.3
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| model_archiver-1.0.3-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details for model_archiver-1.0.3-py2.py3-none-any.whl |
Release files / model_archiver-1.0.3-py2.py3-none-any.whl
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