Quick Start Guide to Large Language Models: Strategies and Best Practices for Using ChatGPT and Other LLMs

by Sinan Ozdemir

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. In Quick 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 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). "By balancing the potential of both open- and closed-source models, Quick Start Guide to Large Language Models stands as a comprehensive guide to understanding and using LLMs, bridging the gap between theoretical concepts and practical application."
-- Giada Pistilli , Principal Ethicist at HuggingFace "A refreshing and inspiring resource. Jam-packed with practical guidance and clear explanations that leave you smarter about this incredible new field."
-- Pete Huang , author of The Neuron Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

288 pages, Paperback

Published September 11, 2023

Reviews

[Aaron Albin · Rating 3 out of 5]

Overall covered core topics well. Second half of the book, mainly advanced topics, seemed to lose focus and delved into too many minor details. Also, I found the python code interjected throughout to be distracting, but I suppose some may find that useful.

[Val Ras · Rating 3 out of 5]

As a 'quick guide' the book fails to deliver. There is just not enough content. It's not a large book, but it could have been even smaller - the pictures are many and often unnecessary and duplicate.

[harsh · Rating 3 out of 5]

Great first book if you want to quickly learn about LLMs. It contains the information about latest LLM models (OpenAI and open source models). The author does a great job of introducing concepts with examples and code snippets whenever needed.