code: def runTest(self):
      document_assembler = (
          DocumentAssembler()
          .setInputCol("text")
          .setOutputCol("document")
      )
  
      tokenizer = (
          Tokenizer().setInputCols("document").setOutputCol("token")
      )
  
      zero_shot_classifier = (
          BartForZeroShotClassification.pretrained()
          .setInputCols(["document", "token"])
          .setOutputCol("class")
          .setCandidateLabels(
              [
                  "urgent",
                  "mobile",
                  "travel",
                  "movie",
                  "music",
                  "sport",
                  "weather",
                  "technology",
              ]
          )
      )
  
      pipeline = Pipeline(
          stages=[document_assembler, tokenizer, zero_shot_classifier]
      )
  
      model = pipeline.fit(self.inputDataset)
      model.transform(self.inputDataset).show()
      light_pipeline = LightPipeline(model)
      annotations_result = light_pipeline.fullAnnotate(self.text)
  
file_path: spark-nlp/python/test/annotator/classifier_dl/bart_for_zero_shot_classification_test.py
imports: import unittest
  import pytest
  from sparknlp.annotator import *
  from sparknlp.base import *
  from test.util import SparkContextForTest
label_desc: Use image node_id 2 for calling the BartForZeroShotClassificationTestSpec obj's underlying member method code with example usage: obj.runTest() without return types