inedTokenizerFast`] which contains most of the main methods. Users should refer to
this superclass for more information regarding those methods

Args:
    vocab_file (`str`):
        [SentencePiece](https://github.com/google/sentencepiece) file (generally has a *.spm* extension) that
        contains the vocabulary necessary to instantiate a tokenizer.
    do_lower_case (`bool`, *optional*, defaults to `True`):
        Whether or not to lowercase the input when tokenizing.
    remove_space (`bool`, *optional*, defaults to `True`):
        Whether or not to strip the text when tokenizing (removing excess spaces before and after the string).
    keep_accents (`bool`, *optional*, defaults to `False`):
        Whether or not to keep accents when tokenizing.
    bos_token (`str`, *optional*, defaults to `"[CLS]"`):
        The beginning of sequence token that was used during pretraining. Can be used a sequence classifier token.

        <Tip>

        When building a sequence using special tokens, this is not the token that is used for the beginning of
        sequence. The token used is the `cls_token`.

        </Tip>

    eos_token (`str`, *optional*, defaults to `"[SEP]"`):
        The end of sequence token. .. note:: When building a sequence using special tokens, this is not the token
        that is used for the end of sequence. The token used is the `sep_token`.
    unk_token (`str`, *optional*, defaults to `"<unk>"`):
        The unknown token. A token that is not in the vocabulary cannot be converted to an ID and is set to be this
        token instead.
    sep_token (`str`, *optional*, defaults to `"[SEP]"`):
        The separator token, which is used when building a sequence from multiple sequences, e.g. two sequences for
        sequence classification or for a text and a question for question answering. It is also used as the last
        token of a sequence built with special tokens.
    pad_token (`str`, *optional*, defaults to `"<pad>"`):
        The token used for padding, for example when batching sequences of different lengths.
    cls_token (`str`, *optional*, defaults to `"[CLS]"`):
        The classifier token which is used when doing sequence classification (classification of the whole sequence
        instead of per-token classification). It is the first token of the sequence when built with special tokens.
    mask_token (`str`, *optional*, defaults to `"[MASK]"`):
        The token used for masking values. This is the token used when training this model with masked language
        modeling. This is the token which the model will try to predict.
c