src/transformers/convert_slow_tokenizer.py/OpenAIGPTConverter/converted
class OpenAIGPTConverter:    def converted(self) -> Tokenizer:
        vocab = self.original_tokenizer.encoder
        merges = list(self.original_tokenizer.bpe_ranks.keys())
        unk_token = self.original_tokenizer.unk_token

        tokenizer = Tokenizer(
            BPE(
                vocab=vocab,
                merges=merges,
                dropout=None,
                unk_token=str(unk_token),
                end_of_word_suffix="</w>",
                fuse_unk=False,
            )
        )

        if tokenizer.token_to_id(str(unk_token)) is not None:
            tokenizer.add_special_tokens([str(unk_token)])

        tokenizer.normalizer = normalizers.BertNormalizer(lowercase=True)
        tokenizer.pre_tokenizer = pre_tokenizers.BertPreTokenizer()
        tokenizer.decoder = decoders.BPEDecoder(suffix="</w>")

        return tokenizer