code: def main():
      train_csv_path = "train.csv"
      eval_csv_path = "eval.csv"
      happy_tt = HappyTextToText("MT5", "google/mt5-base")
  
      train_dataset = load_dataset(
          "persiannlp/parsinlu_translation_en_fa", split="train[0:1999]"
      )
      eval_dataset = load_dataset(
          "persiannlp/parsinlu_translation_en_fa",
          split="validation[0:199]",
      )
  
      generate_csv(train_csv_path, train_dataset)
      generate_csv(eval_csv_path, eval_dataset)
  
      train_args = TTTrainArgs(
          learning_rate=1e-5,
          num_train_epochs=1,
          max_input_length=1024,
          max_output_length=1024,
          # fp16=True,
          # report_to = ('wandb'),
          # project_name = "happy-transformer-examples",
          # run_name = "translation",
          # deepspeed="ZERO-2"
      )
  
      happy_tt.train(train_csv_path, args=train_args)
  
      happy_tt.save("finetuned-model/")
  
imports: import csv
  from happytransformer.happy_text_to_text import HappyTextToText, TTTrainArgs
  from datasets import load_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types