chunk_content: guments class, such as where to save the model to, batch size, learning rate, and number of epochs to train for. The PeftModel doesn’t have the same signature as the base model, so you’ll need to explicitly set remove_unused_columns=False and label_names=["labels"].
  
  
  	Copied
  from transformers import Seq2SeqTrainingArguments
  
  training_args = Seq2SeqTrainingArguments(
      output_dir="your-name/int8-whisper-large-v2-asr",
      per_device_train_bat