class_docstr: Transformers sentiment analysis pipeline returns a list of responses,
  like
      [{'label': 'POSITIVE', 'score': 0.7817379832267761}]
  We need to convert that to a format TextAttack understands, like
      [[0.218262017, 0.7817379832267761]
class_docstr_tok: ["Transformers","sentiment","analysis","pipeline","returns","a","list","of","responses",",","like","[","{","'label","'",":","'POSITIVE","'",",","'score","'",":","0.7817379832267761","}","]","We","need","to","convert","that","to","a","format","TextAttack","understands",",","like","[","[","0.218262017",",","0.7817379832267761","]"]
code: def __init__(self, model):
      self.model = model
  
file_path: TextAttack/examples/attack/attack_camembert.py
imports: import os
  import numpy
  from transformers import AutoTokenizer, TFAutoModelForSequenceClassification, pipeline
  from textattack import Attacker
  from textattack.attack_recipes import PWWSRen2019
  from textattack.datasets import HuggingFaceDataset
  from textattack.models.wrappers import ModelWrapper
label_desc: Use image node_id 1 to create a new HuggingFaceSentimentAnalysisPipelineWrapper object from inherited base classes: ModelWrapper with example: obj = HuggingFaceSentimentAnalysisPipelineWrapper(model)