def load_model_from_config(
    config: Union[Dict[str, Any], Config],
    *,
    meta: Dict[str, Any] = SimpleFrozenDict(),
    vocab: Union["Vocab", bool] = True,
    disable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
    enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
    exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
    auto_fill: bool = False,
    validate: bool = True,
) -> "Language":
    """Create an nlp object from a config. Expects the full config file including
    a section "nlp" containing the settings for the nlp object.

    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 (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
        pipes will be loaded but they won't be run unless you explicitly
        enable them by calling nlp.enable_pipe.
    enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
        pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
    exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
        components won't be loaded.
    auto_fill (bool): Whether to auto-fill config with missing defaults.
    validate (bool): Whether to show config validation errors.
    RETURNS (Language): The loaded nlp object.
    """
    if "nlp" not in config:
        raise ValueError(Errors.E985.format(config=config))
    nlp_config = config["nlp"]
    if "lang" not in nlp_config or nlp_config["lang"] is None:
        raise ValueError(Errors.E993.format(config=nlp_config))
    # This will automatically handle all codes registered via the languages
    # registry, including custom subclasses provided via entry points
    lang_cls = get_lang_class(nlp_config["lang"])
    nlp = lang_cls.from_config(
        config,
        vocab=vocab,
        disable=disable,
        enable=enable,
        exclude=exclude,
        auto_fill=auto_fill,
        validate=validate,
        meta=meta,
    )
    return nlp
Create an nlp object from a config. Expects the full config file including
    a section "nlp" containing the settings for the nlp object.

    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 (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
        pipes will be loaded but they won't be run unless you explicitly
        enable them by calling nlp.enable_pipe.
    enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
        pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
    exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
        components won't be loaded.
    auto_fill (bool): Whether to auto-fill config with missing defaults.
    validate (bool): Whether to show config validation errors.
    RETURNS (Language): The loaded nlp object.
    
spacy/util.py