def METHOD_NAME(self):
    data = load_fridge_dataset()
    task_type = ModelTask.IMAGE_CLASSIFICATION
    class_names = data[ImageColumns.LABEL.value].unique().tolist()
    try:
        model = get_automl_images_mlflow_model(class_names)
    except Exception as exp:
        print(
            'Failed to retrieve or load automl'
            ' images mlflow model: {}'.format(exp)
        )
    run_rai_insights(
        model,
        data[:3],
        ImageColumns.LABEL,
        task_type,
        class_names,
        test_explainer=True,  # enabled as gradcam is faster
    )