GeeeekExplorer/nano-vllm
A lightweight and optimized Python library for fast offline large language model inference, offering comparable or better performance than vLLM with a more readable codebase.
Core Features
Quick Start
pip install git+https://github.com/GeeeekExplorer/nano-vllm.gitDetailed Introduction
Nano-vLLM is an innovative, from-scratch implementation of a lightweight vLLM inference engine. It focuses on delivering high-speed offline inference for large language models, matching or exceeding the performance of the original vLLM while maintaining a significantly more concise and readable Python codebase (around 1,200 lines). The project integrates a comprehensive optimization suite, including prefix caching, tensor parallelism, and leveraging Torch compilation and CUDA graphs, making it an efficient solution for deploying LLMs on various hardware, particularly those with limited resources. Its vLLM-like API ensures ease of adoption for existing vLLM users.