Deploy with vLLM

Key Insight

Serving large language models requires optimizing memory allocation for dynamic sequence lengths. By deploying a model using vLLM, this project demonstrates how PagedAttention prevents physical memory fragmentation of the KV cache. Measuring throughput across various batch sizes reveals how amortizing weight loads from HBM (High-Bandwidth Memory) over concurrent requests increases overall generation efficiency.