A data analyst at a marketing firm wants to leverage a pretrained Google large language model (LLM) in BigQuery to analyze customer feedback data stored in a BigQuery table. They aim to classify sentiment (positive, neutral, negative) based on the textual feedback without having to train a model from scratch. Which approach should the analyst take to implement this with the least setup and configuration?