Model Server for Apache MXNet Documentation

Basic Features

Serving Quick Start - Basic server usage tutorial
Exporting Quick Start - Tutorial that shows you how to export.
Installation - Installation procedures and troubleshooting
Serving Models - Explains how to use mxnet-model-server.
- REST API - Specification on the API endpoint for MMS
- Model Zoo - A collection of MMS .model files that you can use with MMS.
Exporting Models - Explains how to use mxnet-model-export.
Docker - How to use MMS with Docker and cloud services
- Optimized Configuration
Metrics - How to configure logging of metrics

Custom Model Service - Describes how to develop custom inference services.
Client Code Generation - Shows how to use Swagger to create a client API for more than 40 languages. Includes a JavaScript example.
Unit Tests - Housekeeping unit tests for MMS
Load Test - Use JMeter to run MMS through the paces and collect load data

MMS on Fargate, Serverless Inference - The project which illustrates the step-by-step process to launch MMS as a managed inference production service, on ECS Fargate.
LSTM - An example MMS project for a recurrent neural network (RNN) using long short-term memory (LSTM). The project takes JSON inputs for inference against a model trained with a specific vocabulary.
Object Detection - An example MMS project that uses a pretrained Single Shot Multi Object Detection (SSD) model that takes image inputs and infers the types and locations of several classes of objects.