tokenization_flm.py

from transformers import GPT2Tokenizer

class FLMTokenizer(GPT2Tokenizer):
    model_input_names = ["input_ids", "attention_mask"]
    def __init__(
        self,
        vocab_file,
        merges_file,
        errors="replace",
        unk_token="<|endoftext|>",
        bos_token="<|endoftext|>",
        eos_token="<|endoftext|>",
        pad_token=None,
        add_prefix_space=False,
        add_bos_token=False,
        **kwargs,
    ):
        super().__init__(
            vocab_file,
            merges_file,
            errors=errors,
            unk_token=unk_token,
            bos_token=bos_token,
            eos_token=eos_token,
            pad_token=pad_token,
            add_prefix_space=add_prefix_space,
            add_bos_token=add_bos_token,
            **kwargs,
        )
        self.pat = r"""(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+"""