chunk_content:  2.6 MB! This greatly helps with portability, especially when using a very large model to fine-tune (such as BLOOM).
  Next, let’s see how to load the LoRA updated parameters along with our base model for inference. When you wrap a base model
  with PeftModel, modifications are done in-place. To mitigate any concerns that might stem from in-place modifications,
  initialize the base model just like you did earlier and construct the inference model.
  
  