VLLM And stuff given by osmoz

A high-throughput serving engine for LLMs using PagedAttention to optimize GPU memory and inference speeds.

vLLM redefines inference efficiency by implementing PagedAttention (inspired by virtual memory in operating systems) to manage KV cache fragmentation. This architecture allows for 24x higher throughput than Hugging Face Transformers and significantly outperforms Text Generation Inference (TGI) in concurrent request handling. By integrating with the Osmoz stack, developers gain a streamlined deployment pipeline for models like Llama 3 and Mixtral 8x7B, leveraging continuous batching to minimize latency and maximize hardware utilization.

https://github.com/vllm-project/vllm