Unlocking the Future of Chatbots with Falcon, Hugging Face, and Amazon SageMaker
A Step-by-Step Guide to Building a Privacy-Conscious Open-Source Document Chatbot
What is this about?
Over the past two weeks, several exciting developments have transpired in the open-source Large Language Model (LLM) community. The Technology Innovation Institute has unveiled their Falcon models, and Hugging Face has released a new docker container designed for LLM deployment on Amazon SageMaker. These advancements have empowered me to develop a document chatbot that lets users chat with a bot about their private documents. And the best part? Since the model is open-source and hosted on my AWS account, all inference requests stay right within my account, ensuring data privacy.
In this tutorial, I’ll guide you step-by-step through the process needed to create this application. As always, all of my code is freely available and can be found in this GitHub repository. It includes the code for deploying the Falcon model, the code for the app, and a Dockerfile, making it straightforward for you to try this out on your own.
Why is it important?
I’ve been chatting with quite a few organisations over the past weeks who’ve expressed…
