Non-engineers guide: Train a LLaMA 2 chatbot

Introduction

In this tutorial we will show you how anyone can build their own open-source ChatGPT without ever writing a single line of code! We’ll use the LLaMA 2 base model, fine tune it for chat with an open-source instruction dataset and then deploy the model to a chat app you can share with your friends. All by just clicking our way to greatness. 😀

Why is this important? Well, machine learning, especially LLMs (Large Language Models), has witnessed an unprecedented surge in popularity, becoming a critical tool in our personal and business lives. Yet, for most outside the specialized niche of ML engineering, the intricacies of training and deploying these models appears beyond reach. If the anticipated future of machine learning is to be one filled with ubiquitous personalized models, then there's an impending challenge ahead: How do we empower those with non-technical backgrounds to harness this technology independently?

At Hugging Face, we’ve been quietly working to pave the way for this inclusive future. Our suite of tools, including services like Spaces, AutoTrain, and Inference Endpoints, are designed to make the world of machine learning accessible to everyone.

To showcase just how accessible this democratized future is, this tutorial will show you how to use Spaces, AutoTrain and ChatUI to build the chat app. All in just three simple steps, sans a single line of code. For context I’m also not an ML engineer, but a member of the Hugging Face GTM team. If I can do this then you can too! Let's dive in!

Introduction to Spaces

Spaces from Hugging Face is a service that provides easy to use GUI for building and deploying web hosted ML demos and apps. The service allows you to quickly build ML demos using Gradio or Streamlit front ends, upload your own apps in a docker container, or even select a number of pre-configured ML applications to deploy instantly.

We’ll be deploying two of the pre-configured docker application templates from Spaces, AutoTrain and ChatUI.