Imagine you're writing a long story. You might keep a notebook where you jot down important details about the characters, plot points, and settings. This allows you to quickly refer back to these details as you write, rather than having to reread the entire story every time you need to remember something. Key Value (KV) cache is a key factor in the performance of many LLMs, but it also needs to be carefully managed to avoid excessive memory usage. Here's an explanation of KV cache: Core Component: It's a critical component of transformer models, a type of neural network architecture used in many large language models (LLMs). Purpose: To store and retrieve previously computed data during the generation of text or other sequential data. This helps the model generate responses quickly without needing to recalculate information it has already processed. How it Works: Keys and Values: For each token (word or part of a word) in the input text, the model generates a ...