chunk_content: )
  This only saves the incremental 🤗 PEFT weights that were trained, meaning it is super efficient to store, transfer, and load. For example, this bigscience/T0_3B model trained with LoRA on the twitter_complaints subset of the RAFT dataset only contains two files: adapter_config.json and adapter_model.bin. The latter file is just 19MB!
  Easily load your model for inference using the from_pretrained function:
  
  
  	Copied
    from transformers import 