How to Play with LLMs

The second chapter in this extensive guide gives a detailed overview about how to work in the landscape of Large Language Models.

Note: This podcast was created using NotebookLM as an example of how this technology can be used in principle: A podcast about LLMs, generated using an LLM. The chapter was uploaded into the tool which then created this audio file. Pretty interesting, right? However, it may not be 100% justified by the chapter proved by ExpoPlatform. Read for yourself.

Welcome to the second chapter of The Hitchhiker’s Guide to LLMs for Events.

In this release we start to uncover what it really means to work with Large Language Models. Here’s what you’ll find:

• What model size and memory is needed to put LLMs into practice
• The concept of quantization
• Hands-on experimentation with tools and libraries
• Exploration of cloud-based platforms

By the end of this chapter, you’ll have an understanding of the practical landscape of LLMs, as well as the tools needed to easily experiment with their application in the real world. Happy reading!

NOTE: This technical guide is designed for experts and professionals with some understanding of the relevant science.