This tutorial uses Zero-Shot Text Classification and Twilio Programmable SMS to determine whether or not something would be divisive to say at Thanksgiving dinner. It utilizes Transfer Learning with Hugging Face's Transformers NLP library, which provides a wide variety of APIs and pre-trained ML models for Natural Language Processing tasks like classification, information extraction, question answering, summarization, translation, text generation, and more in 100+ languages. The tutorial sets up a Python project and a Twilio number, creates a Flask application to handle inbound text messages, classifies each message using Zero-Shot Classification and multi-class classification, extracts the scores associated with the labels, and returns a response indicating whether or not the input message is safe to say at Thanksgiving dinner. The tutorial also discusses Zero-Shot Learning/Classification, Transfer Learning, and Hugging Face, providing a gentle introduction to these concepts.