Deploy to XCode

We provide Swift Native Interface.

Deploy your own On-device AI iOS application easily. There are only three steps are needed.

1. Embed ZeticMLange.framework to your iOS application project

2. Update project settings to use ZeticMLange.framework

3. Initiailize ZeticMLangeModel with your Model Key and run

Prerequisite

1. Model file

   • You can get Model Key in with mlange_gen at Getting-started page

2. ZeticMLange.framework Library

   • Zetic MLange : ZeticMLange.framework

     • you can download ZeticMLange.framework.zip (click to download). Please unzip the library to your XCode project.

1. Download and embed place ZeticMLange.framework to your project

• e.g. iOS application project structure

  MyiOSApplicationProject
  └── MyiOSApplication
  └── ZeticMLange.framework
  

2. Update project settings to use ZeticMLange.framework to your project

1. Embed ZeticMLange.framework to your application project

2. Set runpath Search Paths to @executable_path/Frameworks

3. Initialize and run ZeticMLangeModel model with your Model Key

• Zetic MLange model running (Swift)

  // 1. Zetic MLange model running
  
  // (1) Load Zetic MLange model
  let model = try ZeticMLangeModel("MLANGE_MODEL_KEY")
  
  // (2) Run model after preparing model inputs
  let inputs: [Data] = [] // Prepare your inputs
  try model.run(inputs)
  
  // (3) Get output data array
  let outputs = model.getOutputDataArray()
  

MLange iOS Sample App

• Please refer MLange iOS sample app for more details

(+) Additional API for MLange-iOS usage

• (This will be updated very soon!)

  • As a default we set the model to use FP16 data type over NPU

  • We set 1 more option for user to choose runtime mode for Better output accuracy.