src/transformers/models/clip/tokenization_clip_fast.py/CLIPTokenizerFast/__init__
class CLIPTokenizerFast:    def __init__(
        self,
        vocab_file=None,
        merges_file=None,
        tokenizer_file=None,
        unk_token="<|endoftext|>",
        bos_token="<|startoftext|>",
        eos_token="<|endoftext|>",
        pad_token="<|endoftext|>",  # hack to enable padding
        **kwargs,
    ):
        super().__init__(
            vocab_file,
            merges_file,
            tokenizer_file=tokenizer_file,
            unk_token=unk_token,
            bos_token=bos_token,
            eos_token=eos_token,
            pad_token=pad_token,
            **kwargs,
        )

        if not isinstance(self.backend_tokenizer.pre_tokenizer, pre_tokenizers.Sequence):
            raise ValueError(
                "The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been"
                " heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using"
                " to be compatible with this version.The easiest way to do so is"
                ' `CLIPTokenizerFast.from_pretrained("path_to_local_folder_or_hub_repo, from_slow=True)`. If you want'
                " to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of"
                " transformers."
            )

        self._wrap_decode_method_backend_tokenizer()