def METHOD_NAME() -> None:
    """A very minimalistic pipeline step.
    Loads a sample dataset, trains a simple classifier and logs
    a couple of metrics.
    """
    neptune_run = zenml.integrations.neptune.experiment_trackers.run_state.get_neptune_run()
    digits = load_digits()
    data = digits.images.reshape((len(digits.images), -1))
    x_train, x_test, y_train, y_test = train_test_split(data, digits.target, test_size=0.3)
    gamma = 0.001
    neptune_run["params/gamma"] = gamma
    model = SVC(gamma=gamma)
    model.fit(x_train, y_train)
    test_acc = model.score(x_test, y_test)
    neptune_run["metrics/val_accuracy"] = test_acc