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LLMOps Strategies for Inference, Serving, and Scalability
This chapter will equip you with the knowledge to make informed decisions about deploying and managing large language models (LLMs), ensuring they are not only powerful and intelligent but also responsive, reliable, and economically viable. These lessons are essential for anyone looking to leverage LLMs to drive value in real-world applications.
In this chapter, we’re going to cover the following main topics:
- Operationalizing inference strategies in LLMOps
- Optimizing model serving for performance
- Increasing model reliability
Operationalizing inference strategies in LLMOps
Inference in the context of LLMs refers to the process of applying a trained model to new data to make predictions ...
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