Llms in Production: From Language Models to Successful Products

Llms in Production: From Language Models to Successful Products
LLMs in Production delivers vital insights into delivering MLOps for LLMs. You'll learn how to operationalize these powerful AI models for chatbots, coding assistants, and more. Find out what makes LLMs so different from traditional software and ML, discover best practices for working with them out of the lab, and dodge common pitfalls with experienced advice. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the book LLMs in Production is the comprehensive guide to LLMs you'll need to effectively guide you to production usage. It takes you through the entire lifecycle of an LLM, from initial concept, to creation and fine tuning, all the way to deployment. You'll discover how to effectively prepare an LLM dataset, cost-efficient training techniques like LORA and RLHF, and how to evaluate your models against industry benchmarks. Learn to properly establish deployment infrastructure and address common challenges like retraining and load testing. Finally, you'll go hands-on with three exciting example projects: a cloud-based LLM chatbot, a Code Completion VSCode Extension, and deploying LLM to edge devices like Raspberry Pi. By the time you're done reading, you'll be ready to start developing LLMs and effectively incorporating them into software. About the reader For data scientists and ML engineers, who know Python and the basics of Kubernetes and cloud deployment. About the author Christopher Brousseau is a Staff MLE at JPMorganChase with a linguistics and localization background. He specializes in linguistically-informed NLP, especially with an international focus and has led successful ML and Data product initiatives<
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LLMs in Production delivers vital insights into delivering MLOps for LLMs. You'll learn how to operationalize these powerful AI models for chatbots, coding assistants, and more. Find out what makes LLMs so different from traditional software and ML, discover best practices for working with them out of the lab, and dodge common pitfalls with experienced advice. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the book LLMs in Production is the comprehensive guide to LLMs you'll need to effectively guide you to production usage. It takes you through the entire lifecycle of an LLM, from initial concept, to creation and fine tuning, all the way to deployment. You'll discover how to effectively prepare an LLM dataset, cost-efficient training techniques like LORA and RLHF, and how to evaluate your models against industry benchmarks. Learn to properly establish deployment infrastructure and address common challenges like retraining and load testing. Finally, you'll go hands-on with three exciting example projects: a cloud-based LLM chatbot, a Code Completion VSCode Extension, and deploying LLM to edge devices like Raspberry Pi. By the time you're done reading, you'll be ready to start developing LLMs and effectively incorporating them into software. About the reader For data scientists and ML engineers, who know Python and the basics of Kubernetes and cloud deployment. About the author Christopher Brousseau is a Staff MLE at JPMorganChase with a linguistics and localization background. He specializes in linguistically-informed NLP, especially with an international focus and has led successful ML and Data product initiatives<
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