How I can save a logistic model for serving? about linfa HOT 6 CLOSED

fn train () {
    let dataset = get_dataset();
    info!("Step: Start Training the model.");
    let model = LogisticRegression::default()
    .max_iterations(500)
    .gradient_tolerance(0.0001)
    .fit(&dataset)
    .expect("Can not train the model");
    let value_model = cbor!(model).unwrap();
    let mut vec_model = Vec::new();
    let _result = ciborium::ser::into_writer(&value_model, &mut vec_model).unwrap();
    // let prediction = model.predict(&dataset.records);
    // println!("{:?}", prediction);
    let write_path = Path::new("model").join("model.cbor");
    fs::write(write_path.clone(), vec_model).unwrap();
    info!("Model saved at {:?}", write_path.as_path());
}

fn load_model() {
    let dataset = get_dataset();
    let mut data: Vec<u8> = Vec::new();
    let path = Path::new("model").join("model.cbor");
    let mut file = File::open(&path).unwrap();
    file.read_to_end(&mut data).unwrap();
    let model_value = ciborium::de::from_reader::<value::Value, _>(&data[..]).unwrap();
    let model: LogisticRegression<f64> = model_value.deserialized().unwrap();
    let result = model.predict(&dataset.records); //THis does not work
}

fn load_model() {
    let dataset = get_dataset();
    let mut data: Vec<u8> = Vec::new();
    let path = Path::new("model").join("model.cbor");
    let mut file = File::open(&path).unwrap();
    file.read_to_end(&mut data).unwrap();
    let model_value = ciborium::de::from_reader::<value::Value, _>(&data[..]).unwrap();
    let model: FittedLogisticRegression<f32, bool> = model_value.deserialized().unwrap(); // THis does not work
    model.predict(dataset.records);
    info!("Model loading was also successful!")
}

let model: FittedLogisticRegression<f32, i32> = model_value.deserialized().unwrap();