Sample iOS App

Once imported, the Swift wrappers les above, using this SwiftNLC

Core ML model, will be easy to execute, as in following code:

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import Foundation

import CoreML

class SwiftNLCModel {

lazy var bagOfWords: BagOfWords = {

return try! JSONDecoder().decode(BagOfWords.se

}()

lazy var intents: [String] = {

return try! JSONDecoder().decode(Array<String>

}()

var lemmatizer = Lemmatizer()

func predict(_ utterance: String) -> (String, Floa

let lemmas = lemmatizer.lemmatize(text: uttera

let embedding = bagOfWords.embed(arrayOfWords:

let model = SwiftNLC()

let size = NSNumber(value: embedding.count)

let mlMultiArrayInput = try! MLMultiArray(shap

for i in 0 ..<size.intValue {

mlMultiArrayInput[i] = NSNumber(floatLiter

}

let prediction = try! model.prediction(input:

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let model = SwiftNLCModel()

@IBAction func go(_ sender: Any) {

if let prediction = model.predict(commandField

intentLabel.text = "\(prediction.0) (\(Str

}

else {

i t tL b lt t " "