class_docstr: Generate potential replacements for a word using a masked language
  model.
code: def __init__(
      self, task="fill-mask", model="xlm-roberta-base", **kwargs
  ):
      self.unmasker = pipeline(task, model)
      super().__init__(**kwargs)
  
file_path: TextAttack/textattack/transformations/word_swaps/chn_transformations/chinese_word_swap_masked.py
imports: from transformers import pipeline
  from .None import WordSwap
label_desc: Use image node_id 1 to create a new ChineseWordSwapMaskedLM object from inherited base classes: WordSwap with example: obj = ChineseWordSwapMaskedLM(task, model)