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I followed the video of Composing advanced models with Create ML Components. I have created the model with let urlParameter = URL(fileURLWithPath: "/path/to/model.pkg") let (training, validation) = dataFrame.randomSplit(by: 0.8) let model = try await transformer.fitted(to: DataFrame(training), validateOn: DataFrame(validation)) { event in guard let tAccuracy = event.metrics[.trainingAccuracy] as? Double else { return } print(tAccuracy) } try transformer.write(model, to: url) print("done") Next goal is to read the model and update it with new dataFrame let urlCSV = URL(fileURLWithPath: "path/to/newData.csv") var model = try transformer.read(from: urlParameters) // loading created model let newDataFrame = try DataFrame(contentsOfCSVFile: urlCSV ) // new dataFrame with features and annotations try await transformer.update(&model, with: newDataFrame) // I want to keep previous learned data and update the model with new try transformer.write(model, to: urlParameters) // the model saves but the only last added dataFrame are saved. Previous one just replaced with new one But looks like I only replace old data with new one. **The Question ** How can add new data to model I created without losing old one ?