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 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). Learn key concepts: pre-training transfer learning fine-tuning attention
embeddings tokenization and more Use APIs and Python to fine-tune and customize LLMs for your
requirements Build a complete neural semantic information retrieval system and attach to
conversational LLMs for retrieval-augmented generation Master advanced prompt engineering
techniques like output structuring chain-ofthought and semantic few-shot prompting Customize
LLM embeddings to build a complete recommendation engine from scratch with user data Construct
and fine-tune multimodal Transformer architectures using opensource LLMs Align LLMs using
Reinforcement Learning from Human and AI Feedback (RLHF RLAIF) Deploy prompts and custom
fine-tuned LLMs to the cloud with scalability and evaluation pipelines in mind 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.
