code: def hf_test_run(
      self, mock_handler, model_name, create_sql, predict_sql
  ):
      # prepare table
      text_spammy = [
          "It is the best time to launch the Robot to get more money. https:\\/\\/Gof.bode-roesch.de\\/Gof",
          "Start making thousands of dollars every week just using this robot. https:\\/\\/Gof.coronect.de\\/Gof",
      ]
  
      text_short = ["I want to dance", "Baking is the best"]
  
      text_long = [
          "Dance is a performing art form consisting of sequences of movement, either improvised or purposefully selected. This movement has aesthetic and often symbolic value.[nb 1] Dance can be categorized and described by its choreography, by its repertoire of movements, or by its historical period or place of origin.",
          "Baking is a method of preparing food that uses dry heat, typically in an oven, but can also be done in hot ashes, or on hot stones. The most common baked item is bread but many other types of foods can be baked. Heat is gradually transferred from the surface of cakes, cookies, and pieces of bread to their center. As heat travels through, it transforms batters and doughs into baked goods and more with a firm dry crust and a softer center. Baking can be combined with grilling to produce a hybrid barbecue variant by using both methods simultaneously, or one after the other. Baking is related to barbecuing because the concept of the masonry oven is similar to that of a smoke pit.",
      ]
  
      df = pd.DataFrame(data=[text_spammy, text_short, text_long]).T
      df.columns = ["text_spammy", "text_short", "text_long"]
  
      self.set_handler(mock_handler, name="pg", tables={"df": df})
  
      # create predictor
      ret = self.run_sql(create_sql)
      assert ret.error_code is None
  
      # wait
      done = False
      for attempt in range(900):
          ret = self.run_sql(
              f"select status from mindsdb.models where name='{model_name}'"
          )
          if len(ret.data) > 0:
              if ret.data[0][0] == "complete":
                  done = True
                  break
              elif ret.data[0][0] == "error":
                  break
          time.sleep(0.5)
      if not done:
          raise RuntimeError("predictor not created")
  
      # use predictor
      ret = self.command_executor.execute_command(
          parse_sql(predict_sql, dialect="mindsdb")
      )
      assert ret.error_code is None
  
file_path: mindsdb/tests/unit/ml_handlers/test_huggingface.py
imports: import time
  from unittest.mock import patch
  import pandas
  from mindsdb_sql import parse_sql
  from tests.unit.executor_test_base import BaseExecutorTest
label_desc: Use image node_id 2 for calling the TestHuggingface obj's underlying member method code with example usage: obj.hf_test_run(mock_handler, model_name, create_sql, predict_sql) without return types