Jumpstart Generative AI Examples

This repository contains code examples for SageMaker Jumpstart Generative AI, a tutorial series designed to help users get started with generative AI using Python and PyTorch.

Module 1: Stable Diffusion with Small Dataset of Cat Images

This module introduces the concept of Stable Diffusion, a powerful generative modeling technique that allows you to generate high-quality images from small datasets. In this module, we use a dataset of cat images and demonstrate how to finetune a stable diffusion model.

Module 2: Stable Diffusion with Large Dataset of Pokemon Images

In this module, we show how Stable Diffusion can be used to generate high-quality images from large datasets. Here, we use a dataset of Pokemon images to demonstrate how to fine-tune the model to generate new, realistic-looking Pokemon.

Module 3: Alexa TM In-Context Learning via Prompt Engineering

This module explores N-shot learning via in-context learning and demonstrates how to use AlexaTM Large Language Model (LLM) to perform natural language understanding (NLU) tasks using zero, one, and few-shot learning. In this module, you will learn how to leverage AlexaTM LLM to improve the performance of virtual assistants by personalizing their responses to users.

Usage

Each module has its own subdirectory containing code examples and instructions for use. Simply navigate to the module you are interested in and follow the instructions in the README file.