def METHOD_NAME(df, model, target, column_count, categorical_dummy_column_names):
    """Gets predictions from the stored AutoKeras model."""
    df_to_predict = df.copy()
    for col in ["__mindsdb_row_id", target]:
        if col in df_to_predict.columns.values.tolist():
            df_to_predict = df_to_predict.drop(col, axis=1)
    if len(df_to_predict.columns) != column_count:
        raise Exception("All feature columns must be defined in the WHERE clause when making predictions")
    # Get dummies for any categorical columns and then populate the missing ones with zeros
    df_with_dummies = pd.get_dummies(df_to_predict)
    for col in categorical_dummy_column_names:  # exception handler for empty columns
        if col not in df_with_dummies.columns.values.tolist():
            df_with_dummies[col] = 0
    return model.predict(df_with_dummies, verbose=2)