ML Training

import { Training } from "std:ai";

fn trainOnDataset(data: Dataset) {
    let job = Training.newJob("gpt-3.5-turbo");
    
    job.setDataset(data);
    job.setHyperparams({
        epochs: 3,
        batchSize: 4,
        learningRate: 0.0001,
    });
    
    job.start();
    print("Training gestartet: {job.id}");
    
    // Auf Abschluss warten
    let result = await job.wait();
    print("Accuracy: {result.accuracy}");
}

import { TrainingService, ONNXConfig } from "std:ai";

fn trainSentimentModel(): void {
    let service = TrainingService.new();
    
    // Training-Daten
    service.addExample("I love this!", "positive");
    service.addExample("This is terrible", "negative");
    
    let config = ONNXConfig {
        epochs: 100,
        batchSize: 32,
        learningRate: 0.001,
        optimizer: "Adam",
    };
    
    let result = service.train("sentiment", config);
    
    match (result) {
        Ok(r) => print("Accuracy: {r.accuracy}"),
        Err(e) => print("Fehler: {e}"),
    }
}