def METHOD_NAME(model_raw,
                 model_convert,
                 tokenizer_raw,
                 tokenizer_convert,
                 path_to_save=None,
                 make_diff_or_recover='diff'):
    make_same_shape(model_raw, model_convert, tokenizer_raw, tokenizer_convert)
    state_dict_raw = model_raw.state_dict()
    state_dict_convert = model_convert.state_dict()
    if make_diff_or_recover == 'diff':
        for key in tqdm.tqdm(state_dict_convert):
            state_dict_convert[key].add_(-state_dict_raw[key])
    elif make_diff_or_recover == 'recover':
        for key in tqdm.tqdm(state_dict_convert):
            state_dict_convert[key].add_(state_dict_raw[key])
    if path_to_save:
        model_convert.save_pretrained(path_to_save, 'pytorch_model.bin')
        tokenizer_convert.save_pretrained(path_to_save)
    return model_convert, tokenizer_convert