def METHOD_NAME(model: str, **kwargs):
    if model == 'gpt2':
        tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
    elif model == 'bloom':
        tokenizer = BloomTokenizerFast.from_pretrained('bigscience/bloom-560m')
    elif model == 'opt':
        tokenizer = AutoTokenizer.from_pretrained("facebook/opt-350m")
    elif model == 'llama':
        pretrain_path = kwargs["pretrain"]
        tokenizer = AutoTokenizer.from_pretrained(pretrain_path)
    else:
        raise ValueError(f'Unsupported model "{model}"')
    tokenizer.pad_token = tokenizer.eos_token
    return tokenizer