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Source channel @githubtrending · Post #15603 · Apr 5

#cplusplus LiteRT-LM is Google's free, high-speed tool for running large language models like Gemma 4 on phones, computers, Raspberry Pi, and more, with GPU boosts, vision/audio support, and tool use for smart apps. It powers AI in Chrome, Pixel Watch, and Chromebook—try it fast via CLI command on Linux, macOS, Windows, or Pi without coding. You benefit by easily deploying fast, private on-device AI for apps, prototyping, or edge projects, saving time and cloud costs. https://github.com/google-ai-edge/LiteRT-LM

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djangoproject

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

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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).

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#testing #async #asyncio #performance #mutlitasking #threads #gevent