Use watsonx to tune Meta llama-2-13b-chat model with CFPB document

This notebook contains the steps and code to demonstrate support of prompt tuning in watsonx. In this notebook, you'll see how to upload a dataset, perform prompt tuning, deploy a prompt-tuned asset, and finally evaluate the deployed asset. Some familiarity with Python is helpful. This notebook uses Python 3.10.