chunk_content: model.print_trainable_parameters()
  # prints trainable params: 56,164 || all params: 4,100,164 || trainable%: 1.369798866581922
  Finally, we can use any training framework we like, or write our own fit loop, to train the peft_model.
  For a complete example, check out this notebook.
  
  timm model
  	
  The timm library contains a large number of pretrained computer vision models.
  Those can also be fine-tuned with PEFT. Let’s check out how this works in p