code: def _load_AnchorText(
      path: Union[str, os.PathLike], predictor: Callable, meta: dict
  ) -> "AnchorText":
      from alibi.explainers import AnchorText
  
      # load explainer
      with open(Path(path, "explainer.dill"), "rb") as f:
          explainer = dill.load(f)
  
      perturb_opts = explainer.perturb_opts
      sampling_strategy = explainer.sampling_strategy
      nlp_sampling = [
          AnchorText.SAMPLING_UNKNOWN,
          AnchorText.SAMPLING_SIMILARITY,
      ]
  
      if sampling_strategy in nlp_sampling:
          # load the spacy model
          import spacy
  
          model = spacy.load(Path(path, "nlp"))
      else:
          # load language model
          import alibi.utils as lang_model
  
          model_class = explainer.model_class
          model = getattr(lang_model, model_class)(preloading=False)
          model.from_disk(Path(path, "language_model"))
  
      # construct perturbation
      perturbation = AnchorText.CLASS_SAMPLER[sampling_strategy](
          model, perturb_opts
      )
  
      # set model, predictor, perturbation
      explainer.model = model
      explainer.reset_predictor(predictor)
      explainer.perturbation = perturbation
      return explainer
  
imports: import copy
  import json
  import numbers
  import os
  from pathlib import Path
  import sys
  from typing import Callable, TYPE_CHECKING, Union
  import warnings
  import dill
  import numpy
  from alibi.version import __version__
label_desc: Use image node_id 9 for calling a global function with example usage: _load_AnchorText(path, predictor, meta) and returns: explainer