chunk_content: tead, it is more efficient to train a smaller number of prompt parameters or use a reparametrization method like low-rank adaptation (LoRA) to reduce the number of trainable parameters. 
  This quicktour will show you 🤗 PEFT’s main features and help you train large pretrained models that would typically be inaccessible on consumer devices. You’ll see how to train the 1.2B parameter bigscience/mt0-large model with LoRA to generate a classification