How to use the kfserving.KFServer function in kfserving

return { "predictions":  preds.argmax(axis=1).tolist() }
        except Exception as e:
            raise Exception("Failed to predict %s" % e)

DEFAULT_MODEL_NAME = "model"
DEFAULT_LOCAL_MODEL_DIR = "/tmp/model"

parser = argparse.ArgumentParser(parents=[kfserving.kfserver.parser])
parser.add_argument('--model_dir', required=True,
                    help='A URI pointer to the model binary')
args, _ = parser.parse_known_args()

if __name__ == "__main__":
    model = SignsModel("signs",args.model_dir)
    # Set number of workers to 1 as model is quite large
    kfserving.KFServer(workers=1).start([model])

return { "predictions":  preds.argmax(axis=1).tolist() }
        except Exception as e:
            raise Exception("Failed to predict %s" % e)

DEFAULT_MODEL_NAME = "model"
DEFAULT_LOCAL_MODEL_DIR = "/tmp/model"

parser = argparse.ArgumentParser(parents=[kfserving.kfserver.parser])
parser.add_argument('--model_dir', required=True,
                    help='A URI pointer to the model binary')
args, _ = parser.parse_known_args()

if __name__ == "__main__":
    model = MnistModel("mnist",args.model_dir)
    # Set number of workers to 1 as model is quite large
    kfserving.KFServer(workers=1).start([model])