def METHOD_NAME(example, tokenizer, max_seq_length=512, do_evalute=False):
    """
    Builds model inputs from a sequence.
    A BERT sequence has the following format:
    - single sequence: ``[CLS] X [SEP]``
    Args:
        example(obj:`list(str)`): The list of text to be converted to ids.
        tokenizer(obj:`PretrainedTokenizer`): This tokenizer inherits from :class:`~paddlenlp.transformers.PretrainedTokenizer`
            which contains most of the methods. Users should refer to the superclass for more information regarding methods.
        max_seq_len(obj:`int`): The maximum total input sequence length after tokenization.
            Sequences longer than this will be truncated, sequences shorter will be padded.
        is_test(obj:`False`, defaults to `False`): Whether the example contains label or not.
    Returns:
        input_ids(obj:`list[int]`): The list of query token ids.
        token_type_ids(obj: `list[int]`): List of query sequence pair mask.
    """
    result = []
    for key, text in example.items():
        if "label" in key:
            # do_evaluate
            result += [example["label"]]
        else:
            # do_train
            encoded_inputs = tokenizer(text=text, max_seq_len=max_seq_length)
            input_ids = encoded_inputs["input_ids"]
            token_type_ids = encoded_inputs["token_type_ids"]
            result += [input_ids, token_type_ids]
    return result