/generative-ai-prompt-engineering

Sample code that helps us explore the world of generative AI through prompt engineering. It provides the resources for experimenting with this emerging skill through demos and sample applications such as simple chatbots.

Primary LanguageJupyter NotebookMIT No AttributionMIT-0

Generative AI - Prompt Engineering

Welcome.

Sample code that helps us explore the world of generative AI through prompt engineering. It provides the resources for experimenting with this emerging skill through demos and sample applications such as simple chatbots.

Notebooks:

  • Prompt Engineering - Chatbot
    • This notebook has been designed, written and tested to run for free on Amazon SageMaker Studio Lab with GPU. Studio Lab is a free machine learning (ML) development environment that provides compute and storage (up to 15GB) at no cost with NO credit card required.
    • In this notebook we will look at a few prompt engineering techniques. We will experiment by loading a - relatively small - 3 billion parameter Large Language Model (LLM) within the notebook environment itself and using zero-shot, one-shot and few-shot in context learning prompts and see the response from the model. We will then use the techniques we have explored to build a simple chatbot!

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.