def build_inputs_with_special_tokens(
        self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None
    ) -> List[int]:
        """
        Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and
        adding special tokens. A CLIP sequence has the following format:

        - single sequence: `<|startoftext|> X <|endoftext|>`

        Pairs of sequences are not the expected use case, but they will be handled without a separator.

        Args:
            token_ids_0 (`List[int]`):
                List of IDs to which the special tokens will be added.
            token_ids_1 (`List[int]`, *optional*):
                Optional second list of IDs for sequence pairs.

        Returns:
            `List[int]`: List of [input IDs](../glossary#input-ids) with the appropriate special tokens.
        """
        bos_token = [self.bos_token_id]
        eos_token = [self.eos_token_id]

        if token_ids_1 is None:
            return bos_token + token_ids_0 + eos_token
        return bos_token + token_ids_0 + eos_token + eos_token + token_ids_1 + eos_token

        Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and
        adding special tokens. A CLIP sequence has the following format:

        - single sequence: `<|startoftext|> X <|endoftext|>`

        Pairs of sequences are not the expected use case, but they will be handled without a separator.

        Args:
            token_ids_0 (`List[int]`):
                List of IDs to which the special tokens will be added.
            token_ids_1 (`List[int]`, *optional*):
                Optional second list of IDs for sequence pairs.

        Returns:
            `List[int]`: List of [input IDs](../glossary#input-ids) with the appropriate special tokens.
        
dpkd/transformers/src/transformers/models/clip/tokenization_clip.py