from transformers import AutoConfig
from transformers.models.auto.tokenization_auto import AutoTokenizer


def is_model_on_hub(
    model_name: str, revision: str, token: str = None, trust_remote_code=False, test_tokenizer=False
) -> tuple[bool, str]:
    """Checks if the model model_name is on the hub, and whether it (and its tokenizer) can be loaded with AutoClasses."""
    try:
        config = AutoConfig.from_pretrained(
            model_name, revision=revision, trust_remote_code=trust_remote_code, token=token
        )
        if test_tokenizer:
            try:
                tk = AutoTokenizer.from_pretrained(
                    model_name, revision=revision, trust_remote_code=trust_remote_code, token=token
                )
            except ValueError as e:
                return (False, f"uses a tokenizer which is not in a transformers release: {e}", None)
            except Exception as e:
                return (
                    False,
                    "'s tokenizer cannot be loaded. Is your tokenizer class in a stable transformers release, and correctly configured?",
                    None,
                )
        return True, None, config

    except ValueError:
        return (
            False,
            "needs to be launched with `trust_remote_code=True`. For safety reason, we do not allow these models to be automatically submitted to the leaderboard.",
            None,
        )

    except Exception as e:
        return False, "was not found on hub!", None