code: def main():
      train_txt_path = "train.txt"
      eval_txt_path = "eval.txt"
  
      train_dataset = load_dataset("billsum", split="train[0:1999]")
      eval_dataset = load_dataset("billsum", split="test[0:199]")
  
      generate_txt_file(train_txt_path, train_dataset)
      generate_txt_file(eval_txt_path, eval_dataset)
  
      happy_wp = HappyWordPrediction(
          model_type="DISTILBERT", model_name="distilbert-base-uncased"
      )
  
      train_args = WPTrainArgs(
          learning_rate=1e-5,
          num_train_epochs=1,
          # fp16=True,
          # report_to = ('wandb'),
          # project_name = "happy-transformer-examples",
          # run_name = "word-prediction",
          # deepspeed="ZERO-2"
      )
  
      happy_wp.train(
          train_txt_path, args=train_args, eval_filepath=eval_txt_path
      )
  
      happy_wp.save("finetuned-model/")
  
imports: import csv
  from datasets import load_dataset
  from happytransformer.happy_word_prediction import HappyWordPrediction, WPTrainArgs
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types