
import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase    ,		__lowerCAmelCase    ,		**__lowerCAmelCase							):
    snake_case__						=				AutoConfig.from_pretrained(__lowerCAmelCase    ,		**__lowerCAmelCase							)
    snake_case__						=				AutoModelForSeqaSeqLM.from_config(__lowerCAmelCase							)
    model.save_pretrained(__lowerCAmelCase							)
    AutoTokenizer.from_pretrained(__lowerCAmelCase							).save_pretrained(__lowerCAmelCase							)
    return model


if __name__ == "__main__":
     fire.Fire(save_randomly_initialized_version)





from __future__ import annotations





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase    ,		__lowerCAmelCase    ,		__lowerCAmelCase							):
    if (voltage, current, resistance).count(0							) != 1:
        raise ValueError("One and only one argument must be 0"							)
    if resistance < 0:
        raise ValueError("Resistance cannot be negative"							)
    if voltage == 0:
        return {"voltage": float(current * resistance							)}
    elif current == 0:
        return {"current": voltage / resistance}
    elif resistance == 0:
        return {"resistance": voltage / current}
    else:
        raise ValueError("Exactly one argument must be 0"							)


if __name__ == "__main__":
     import doctest

     doctest.testmod()



