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This chapter provides a comprehensive guide to setting up the infrastructure necessary to support large language models (LLMs) in finance, where performance, scalability, and compliance are critical. Given the intense computational requirements of LLMs and the sensitivity of financial data, establishing the right infrastructure is essential for successful deployment. The chapter begins with an in-depth look at hardware requirements, covering the processing power, storage, and memory configurations that enable high-performance LLMs to operate efficiently. Following this, readers are introduced to the software stack, focusing on libraries, frameworks, and model management tools that streamline model development, deployment, and lifecycle management.

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Infrastructure Setup for LLMs

  • 章节

  • 发表日期：

    2025年

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  • Brindha Priyadarshini Jeyaraman

摘要

This chapter provides a comprehensive guide to setting up the infrastructure necessary to support large language models (LLMs) in finance, where performance, scalability, and compliance are critical. Given the intense computational requirements of LLMs and the sensitivity of financial data, establishing the right infrastructure is essential for successful deployment. The chapter begins with an in-depth look at hardware requirements, covering the processing power, storage, and memory configurations that enable high-performance LLMs to operate efficiently. Following this, readers are introduced to the software stack, focusing on libraries, frameworks, and model management tools that streamline model development, deployment, and lifecycle management.