The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products. Large Language Models (LLMs) like ChatGPT are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them. InQuick Start Guide to Large Language Models, pioneering data scientist and AI entrepreneur Sinan Ozdemir clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems. Ozdemir brings together all you need to get started, even if you have no direct experience with LLMs: step-by-step instructions, best practices, real-world case studies, hands-on exercises, and more. Along the way, he shares insights into LLMs' inner workings to help you optimize model choice, data formats, parameters, and performance. You'll find even more resources on the companion website, including sample datasets and code for working with open- and closed-source LLMs such as those from OpenAI (GPT-4 and ChatGPT), Google (BERT, T5, and Bard), EleutherAI (GPT-J and GPT-Neo), Cohere (the Command family), and Meta (BART and the LLaMA family). Who is this book for, you ask? Well, my answer is simple: anyone who shares a curiosity about LLMs, the willing coder, the relentless learner. Whether you’re already entrenched in Machine Learning or you’re on the edge, dipping your toes into this vast ocean, this book is your guide, your map to navigate the waters of LLMs. However, I’ll level with you: To get the most out of this journey, having some experience with Machine Learning and Python will be incredibly beneficial.