Introduction

Welcome to our workshop! In this workshop we'll be using the open-sourced IBM Granite AI foundation models for a number of use cases that demonstrates the value of generative AI.

By the end of this workshop, you will be able to:

• Summarize a text document using text summarization
• Generate specific information from a large document using the RAG technique
• Predict future trends using time series forecasting
• Generate programming code (Bash) by prompting a code model

About this workshop

The introductory page of the workshop is broken down into the following sections:

• Agenda
• Technology Used
• Credits

Agenda

Lab 0: Pre-work	Pre-work for the workshop
Lab 1: Document Summarization with Granite	Learn how to use an AI model to summarize a work of literature
Lab 2: Retrieval Augmented Generation (RAG) with Langchain	Learn how to generate specific information from a large document
Lab 3: Energy Demand Forecasting with Granite Timeseries (TTM)	Learn how to predict future trends using time series forecasting
Lab 4: Generating Bash Code with Granite Code	Learn how to use an AI model to generate programming code

Technology Used

The technology used in the workshop is as follows:

• Google Colab
• IBM Granite AI foundation models
• Jupyter notebooks
• LangChain
• Ollama
• Replicate

Credits

• BJ Hargrave
• Martin Hickey
• Ming Zhao
• The notebooks used in this workshop are versions of notebooks from the IBM Granite Community modified for the workshop needs