def METHOD_NAME(self):
    test_df = self.load_classifier_dl_dataset()
    train_df = test_df
    train_df.columns = ["y", "text"]
    test_df.columns = ["y", "text"]
    pipe = nlu.load(
        "xx.embed_sentence.labse train.classifier",
        verbose=True,
    )
    pipe["classifier_dl"].setMaxEpochs(2)
    pipe = pipe.fit(train_df)
    df = pipe.predict(test_df)
    pipe.print_info()
    print(df.columns)
    for c in df.columns:
        print(df[c])