 Summary generation  - This model achieves ROUGE-1 / ROUGE-2 / ROUGE-L of 37.28 / 18.58 / 34.53 on the Gigaword test set; this is pretty good when compared to PEGASUS, `google/pegasus-gigaword`, which achieves 39.12 / 19.86 / 36.24.  - To achieve these results, generate text using the code below. `text_list` is a list of input text string.  ``` input_ids_list = tokenizer(text_list, truncation=True, max_length=128,          return_tensors='pt', padding=True)['input_ids'] output_ids_list = model.generate(input_ids_list, min_length=0) outputs_list = tokenizer.batch_decode(output_ids_list, skip_special_tokens=True,          clean_up_tokenization_spaces=False) ```