What are the different ways to use and finetune pretrained large language models (LLMs)? The three most common ways to use and finetune pretrained LLMs include a feature-based approach, in-context prompting, and updating a subset of the model parameters. First, most pretrained LLMs or language transformers can be utilized without the need for further finetuning. For instance, we can employ a feature-based method to train a new downstream model, such as a linear classifier, using embeddings generated by a pretrained transformer. Second, we can showcase examples of a new task within the input …