





from argparse import ArgumentParser

from . import BaseTransformersCLICommand






def 	lowerCamelCase_		(							_UpperCamelCase					)						->		Optional[Any]:






				"""simple docstring"""


				return DownloadCommand(args.model					,							args.cache_dir					,							args.force					,							args.trust_remote_code					)





class    __lowerCAmelCase			(     _a	):






			@staticmethod
			def      lowerCamelCase    (__magic_name__       )	->  Tuple:


							'''simple docstring'''



							snake_case_		:       Tuple           =    parser.add_parser('''download'''       )
							download_parser.add_argument(
							    '''--cache-dir'''   ,				type=__magic_name__   ,				default=__magic_name__   ,				help='''Path to location to store the models'''       )
							download_parser.add_argument(
							    '''--force'''   ,				action='''store_true'''   ,				help='''Force the model to be download even if already in cache-dir'''       )
							download_parser.add_argument(
							    '''--trust-remote-code'''   ,				action='''store_true'''   ,				help='''Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you\'ve reviewed the code as it will execute on your local machine'''   ,				)
							download_parser.add_argument('''model'''   ,				type=__magic_name__   ,				help='''Name of the model to download'''       )
							download_parser.set_defaults(func=__magic_name__       )






			def __init__(self   ,				__magic_name__   ,				__magic_name__   ,				__magic_name__   ,				__magic_name__       )	->  Union[str, Any]:


							'''simple docstring'''



							snake_case_		:       Optional[int]           =    model
							snake_case_		:       List[str]           =    cache
							snake_case_		:       List[str]           =    force
							snake_case_		:       Optional[Any]           =    trust_remote_code






			def      lowerCamelCase    (self       )	->  int:


							'''simple docstring'''



							from ..models.auto import AutoModel, AutoTokenizer

							AutoModel.from_pretrained(
							    self._model   ,				cache_dir=self._cache   ,				force_download=self._force   ,				trust_remote_code=self._trust_remote_code       )
							AutoTokenizer.from_pretrained(
							    self._model   ,				cache_dir=self._cache   ,				force_download=self._force   ,				trust_remote_code=self._trust_remote_code       )








__a:     List[Any]   					=					{
    '''Pillow''': '''Pillow''',
    '''accelerate''': '''accelerate>=0.11.0''',
    '''compel''': '''compel==0.1.8''',
    '''black''': '''black~=23.1''',
    '''datasets''': '''datasets''',
    '''filelock''': '''filelock''',
    '''flax''': '''flax>=0.4.1''',
    '''hf-doc-builder''': '''hf-doc-builder>=0.3.0''',
    '''huggingface-hub''': '''huggingface-hub>=0.13.2''',
    '''requests-mock''': '''requests-mock==1.10.0''',
    '''importlib_metadata''': '''importlib_metadata''',
    '''invisible-watermark''': '''invisible-watermark''',
    '''isort''': '''isort>=5.5.4''',
    '''jax''': '''jax>=0.2.8,!=0.3.2''',
    '''jaxlib''': '''jaxlib>=0.1.65''',
    '''Jinja2''': '''Jinja2''',
    '''k-diffusion''': '''k-diffusion>=0.0.12''',
    '''torchsde''': '''torchsde''',
    '''note_seq''': '''note_seq''',
    '''librosa''': '''librosa''',
    '''numpy''': '''numpy''',
    '''omegaconf''': '''omegaconf''',
    '''parameterized''': '''parameterized''',
    '''protobuf''': '''protobuf>=3.20.3,<4''',
    '''pytest''': '''pytest''',
    '''pytest-timeout''': '''pytest-timeout''',
    '''pytest-xdist''': '''pytest-xdist''',
    '''ruff''': '''ruff>=0.0.241''',
    '''safetensors''': '''safetensors''',
    '''sentencepiece''': '''sentencepiece>=0.1.91,!=0.1.92''',
    '''scipy''': '''scipy''',
    '''onnx''': '''onnx''',
    '''regex''': '''regex!=2019.12.17''',
    '''requests''': '''requests''',
    '''tensorboard''': '''tensorboard''',
    '''torch''': '''torch>=1.4''',
    '''torchvision''': '''torchvision''',
    '''transformers''': '''transformers>=4.25.1''',
    '''urllib3''': '''urllib3<=2.0.0''',
}