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Source channel @githubtrending · Post #15263 · Nov 2

#python#deep_learning#inference#llm#nlp#pytorch#transformer Nano-vLLM is a small, fast, and easy-to-understand tool for running large language models offline. It matches the speed of bigger systems like vLLM but uses only about 1,200 lines of clean Python code, making it simple to read and modify. It includes smart features like prefix caching and tensor parallelism to boost performance. You can install it easily and run models like Qwen3-0.6B on your own GPU. This tool is great if you want fast, efficient AI inference without complex setups, ideal for learning, research, or small deployments on limited hardware. https://github.com/GeeeekExplorer/nano-vllm

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djangoproject

@djangoproject · Post #270 · 02/26/2017, 08:08 AM

https://www.obeythetestinggoat.com/testing-async-asyncio-and-performance.html #Testing, #async, #asyncio, and #performance Sun 27 December 2015 By Harry I recently did some experimenting with asyncio, and wanted to report back on how I got on with writing tests for it. While I was at it I was also able to compare its performance with a couple of other approaches to #mutlitasking in Python, namely #threads and #gevent, so I'll report on that here too. (tl;dr: it's much of a muchness).