code: def example_2_3():
      happy_tc = HappyTextClassification(
          model_type="DISTILBERT",
          model_name="distilbert-base-uncased-finetuned-sst-2-english",
          num_labels=2,
      )  # Don't forget to set num_labels!
      args = TCEvalArgs(
          save_preprocessed_data=False
      )  # for demonstration -- not needed
      result = happy_tc.eval("../../data/tc/train-eval.csv", args=args)
      print(
          type(result)
      )  # <class 'happytransformer.happy_trainer.EvalResult'>
      print(result)  # EvalResult(eval_loss=0.007262040860950947)
      print(result.loss)
  
file_path: happy-transformer/examples/text_classification/readme_examples.py
imports: from happytransformer import HappyTextClassification, TCTrainArgs, TCEvalArgs, TCTestArgs
  from happytransformer import HappyTokenClassification
label_desc: Use image node_id 4 for calling a global function with example usage: example_2_3() without return types