vllm.tokenizers ¶

def get_tokenizer(
    tokenizer_name: str | Path,
    *args,
    tokenizer_cls: type[_T] = TokenizerLike,  # type: ignore[assignment]
    trust_remote_code: bool = False,
    revision: str | None = None,
    download_dir: str | None = None,
    **kwargs,
) -> _T:
    """Gets a tokenizer for the given model name via HuggingFace or ModelScope."""
    tokenizer_mode, tokenizer_name, args, kwargs = cached_resolve_tokenizer_args(
        tokenizer_name,
        *args,
        trust_remote_code=trust_remote_code,
        revision=revision,
        download_dir=download_dir,
        **kwargs,
    )

    if tokenizer_cls == TokenizerLike:
        tokenizer_cls_ = TokenizerRegistry.load_tokenizer_cls(tokenizer_mode)
    else:
        tokenizer_cls_ = tokenizer_cls

    tokenizer = tokenizer_cls_.from_pretrained(tokenizer_name, *args, **kwargs)
    if not tokenizer.is_fast:
        logger.warning(
            "Using a slow tokenizer. This might cause a significant "
            "slowdown. Consider using a fast tokenizer instead."
        )

    return tokenizer  # type: ignore