vllm
2 free lessons tagged vllm across AI. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.
Grammars, Stacks, and Making It Free
Recursive formats need a machine with a stack, and a stack breaks the precomputed index because the mask now depends on context. This lesson covers context-free grammars and pushdown automata, XGrammar's split between context-independent and context-dependent tokens, why overlapping grammar work with the GPU makes overhead near zero, and how this interacts with batching and speculative decoding.
LLM Inference Internals: KV Cache, Sampling, and Serving at Scale
A deep dive into how large language models actually run in production — why prefill is fast and decode is slow, how the KV cache works, sampling strategies like temperature and top-p, speculative decoding, and continuous batching with vLLM.