code: def load_model_from_path(model_path, meta=False, **overrides):
      
      if not meta:
          meta = get_model_meta(model_path)
      cls = get_lang_class(meta["lang"])
      nlp = cls(meta=meta, **overrides)
      pipeline = meta.get("pipeline", [])
      disable = overrides.get("disable", [])
      if pipeline is True:
          pipeline = nlp.Defaults.pipe_names
      elif pipeline in (False, None):
          pipeline = []
      for name in pipeline:
          if name not in disable:
              config = meta.get("pipeline_args", {}).get(name, {})
              component = nlp.create_pipe(name, config=config)
              nlp.add_pipe(component, name=name)
      return nlp.from_disk(model_path)
docs: Load a model from a data directory path. Creates Language class with
      pipeline from meta.json and then calls from_disk() with path.