      # 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, auto_fill=auto_fill, validate=validate,
      )
      return nlp, nlp.resolved
  
  
  def load_model_from_init_py(
 
</s> remove     nlp, _ = load_model_from_config(config, vocab=vocab, disable=disable)
    return nlp.from_disk(model_path, exclude=disable)
 </s> add     nlp, _ = load_model_from_config(
        config, vocab=vocab, disable=disable, exclude=exclude
    )
    return nlp.from_disk(model_path, exclude=exclude) </s> remove         data_path, vocab=vocab, meta=meta, disable=disable, config=config
 </s> add         data_path,
        vocab=vocab,
        meta=meta,
        disable=disable,
        exclude=exclude,
        config=config, </s> remove         self.pipeline.insert(pipe_index, (name, pipe_component))
 </s> add         self._pipeline.insert(pipe_index, (name, pipe_component))
        config,
        vocab=vocab,
        disable=disable,
        exclude=exclude,
        auto_fill=auto_fill,
        validate=validate,
      # 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,
        exclude=exclude,
        auto_fill=auto_fill,
        validate=validate,
      )
      return nlp, nlp.resolved
  
  
  def load_model_from_init_py(
keep keep keep keep replace keep keep keep keep keep
 Allow loaded but disabled components 
spacy/util.py