  
  
  def is_package(name: str) -> bool:
      """Check if string maps to a package installed via pip.
  
      name (str): Name of package.
 
</s> remove     """Load a model from an installed package."""
 </s> add     """Load a model from an installed package.

    name (str): The package name.
    vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
        a new Vocab object will be created.
    disable (Iterable[str]): Names of pipeline components to disable.
    config (Dict[str, Any] / Config): Config overrides as nested dict or dict
        keyed by section values in dot notation.
    RETURNS (Language): The loaded nlp object.
    """ </s> remove     """Load a full config from a string."""
 </s> add     """Load a full config from a string. Wrapper around Thinc's Config.from_str.

    text (str): The string config to load.
    interpolate (bool): Whether to interpolate and resolve variables.
    RETURNS (Config): The loaded config.
    """ </s> remove     pipeline from config.cfg and then calls from_disk() with path."""
 </s> add     pipeline from config.cfg and then calls from_disk() with path.

    name (str): Package name or model path.
    meta (Dict[str, Any]): Optional model meta.
    vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
        a new Vocab object will be created.
    disable (Iterable[str]): Names of pipeline components to disable.
    config (Dict[str, Any] / Config): Config overrides as nested dict or dict
        keyed by section values in dot notation.
    RETURNS (Language): The loaded nlp object.
    """
def get_model_meta(path: Union[str, Path]) -> Dict[str, Any]:
    """Get model meta.json from a directory path and validate its contents.

    path (str / Path): Path to model directory.
    RETURNS (Dict[str, Any]): The model's meta data.
    """
    model_path = ensure_path(path)
    return load_meta(model_path / "meta.json")


  
  
def get_model_meta(path: Union[str, Path]) -> Dict[str, Any]:
    """Get model meta.json from a directory path and validate its contents.

    path (str / Path): Path to model directory.
    RETURNS (Dict[str, Any]): The model's meta data.
    """
    model_path = ensure_path(path)
    return load_meta(model_path / "meta.json")


  def is_package(name: str) -> bool:
      """Check if string maps to a package installed via pip.
  
      name (str): Name of package.
keep add keep keep keep keep
 Update docs and util consistency 
spacy/util.py