code: def _download_and_prepare(self, dl_manager):
      if self.config_name == "default":
          logger.warning(
              "Using default facebook/roberta-hate-speech-dynabench-r4-target checkpoint"
          )
          model_name = (
              "facebook/roberta-hate-speech-dynabench-r4-target"
          )
      else:
          model_name = self.config_name
      self.toxic_classifier = pipeline(
          "text-classification",
          model=model_name,
          top_k=99999,
          truncation=True,
      )
  
file_path: evaluate/measurements/toxicity/toxicity.py
imports: import datasets
  from transformers import pipeline
  import evaluate
label_desc: Use image node_id 2 for calling the Toxicity obj's underlying member method code with example usage: obj._download_and_prepare(dl_manager) without return types