text: def trainable_params(m):
      return filter(lambda x: x.requires_grad, model.parameters())
  
  def count_parameters(m):
      total = int(sum(p.numel() for p in m.parameters()))
      trainable = int(sum(p.numel() for p in m.parameters() if p.requires_grad))
      return f'total: {total}, trainable: {trainable}'
  