chunk_content:  much more efficient LoRA is compared to fully training the model!
  
  
  	Copied
  model = get_peft_model(model, config)
  model.print_trainable_parameters()
  "trainable params: 15728640 || all params: 1559033600 || trainable%: 1.0088711365810203"
  Now you’re ready to define some training hyperparameters in the Seq2SeqTrainingArguments class, such as where to save the model to, batch size, learning rate, and number of epochs to train for. The PeftModel d