Название: LLMOps: Managing Large Language Models in Production (Early Release)
Автор: Abi Aryan
Издательство: O’Reilly Media, Inc.
Год: 2025-01-29
Страниц: 100
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

Are you wrestling with the complexities of deploying and managing large language models? The rapid evolution of AI technologies demands robust solutions that can streamline development, enhance security, and scale effectively. However, the lack of clear guidance can make navigating this landscape daunting.

Enter this much needed book by Abi Aryan—a vital resource poised to transform your approach to MLOps. This comprehensive guide equips you with the essential techniques and tools to develop, deploy, and manage large language models efficiently. Whether you're a seasoned AI practitioner or just stepping into the field, this book is your gateway to mastering LLMOps, ensuring your projects are not just functional but flourishing.

Large language models (LLMs) are the much-hyped rockstars of the AI world. They’re making headlines daily for their incredible abilities to generate text, hold conversations, and understand complex queries. However, as we said in the Preface, their rise to popularity is no accident; they’re transforming how we interact with technology and pushing the boundaries of what machine learning models can do.

But here’s the catch: while these models are impressive, scaling them up and managing them in production is no walk in the park. The leap from a research project to a fully fledged, reliable tool is filled with obstacles. We’re talking about meeting enormous computational requirements, managing complex data, and ensuring that everything runs smoothly and securely.

By reading, you will:
Gain a robust understanding of data versioning, experiment tracking, and model deployment
Understand the architectures of models like OpenAI ChatGPT and how to fine-tune them
Learn how to implement critical security measures and comply with privacy regulations
Explore using Flask and Kubernetes to deploy models, optimizing for both performance and cost
Discover how to integrate cutting-edge tools like ChatGPT and Whisper