Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG
Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG by Louis-François Bouchard, Louie Peters
English | May 17, 2024 | ISBN: 9798327302143, 9798324731472, ASIN: B0D6BVJLHJ | PDF | 485 pages | 5.8 MB
English | May 17, 2024 | ISBN: 9798327302143, 9798324731472, ASIN: B0D6BVJLHJ | PDF | 485 pages | 5.8 MB
With amazing feedback from industry leaders, this book is an end-to-end resource for anyone looking to enhance their skills or dive into the world of AI and develop their understanding of Generative AI and Large Language Models (LLMs). It explores various methods to adapt "foundational" LLMs to specific use cases with enhanced accuracy, reliability, and scalability. Written by over 10 people on our Team at Towards AI and curated by experts from Activeloop, LlamaIndex, Mila, and more, it is a roadmap to the tech stack of the future.
The book aims to guide developers through creating LLM products ready for production, leveraging the potential of AI across various industries. It is tailored for readers with an intermediate knowledge of Python.
What's Inside this 470-page Book?
- Hands-on Guide on LLMs, Prompting, Retrieval Augmented Generation (RAG) & Fine-tuning
- Roadmap for Building Production-Ready Applications using LLMs
- Fundamentals of LLM Theory
- Simple-to-Advanced LLM Techniques & Frameworks
- Code Projects with Real-World Applications
- Colab Notebooks that you can run right away
- Community access and our own AI Tutor
Whether you're looking to enhance your skills or dive into the world of AI for the first time as a programmer or software student, our book is for you. From the basics of LLMs to mastering fine-tuning and RAG for scalable, reliable AI applications, we guide you every step of the way.