
KV Cache in LLMs
I am Amit Shekhar , Founder @ Outcome School , I have taught and mentored many developers, and their efforts landed them high-paying tech jobs, helped many tech companies in solving their unique problems, and created many open-source libraries being used by top companies. I am passionate about sharing knowledge through open-source, blogs, and videos. I teach AI and Machine Learning , and Android at Outcome School. Join Outcome School and get high paying tech job: Outcome School AI and Machine Learning Program Outcome School Android Program In this blog, we will learn about KV Cache - where K stands for Key and V stands for Value - and why it is used in Large Language Models (LLMs) to speed up text generation. We will start with how LLMs generate text one token at a time, understand the role of Key, Value, and Query inside the model, see the problem of repeated computation through an example, and then walk through how KV Cache solves this problem by storing and reusing past results. Let
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