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Source channel @githubtrending · Post #15348 · Dec 20

#go#gemma3#go#gpt_oss#granite4#llama#llama3#llm#on_device_ai#phi3#qwen3#qwen3vl#sdk#stable_diffusion#vlm NexaSDK runs AI models locally on CPUs, GPUs, and NPUs with a single command, supports GGUF/MLX/.nexa formats, and offers NPU-first Android and macOS support for fast, multimodal (text, image, audio) inference, plus an OpenAI‑compatible API for easy integration. This gives you low-latency, private on-device AI across laptops, phones, and embedded systems, reduces cloud costs and data exposure, and lets you deploy and test new models immediately on target hardware for faster development and better user experience. https://github.com/NexaAI/nexa-sdk

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djangoproject

@djangoproject · Post #388 · 07/19/2017, 08:35 PM

https://www.youtube.com/watch?v=D-5V7s0GflU Look mum no hands! From blinking LEDs to a bike speedometer with #MicroPython In this talk I will show you how to use a micro-controller to build a wifi enabled speedometer for your bike, using MicroPython. And some hardware. And a bike (maybe). I will introduce you to the world of MicroPython: a python distribution that runs on micro-controllers. Micro-controllers are small computers that are all around us: in cars, TVs, and your internet connected fridge. We will start with making LEDs blink, then serve webpages, build an interrupt handler and finally put it all together to make a wifi enabled speedometer for a bike.

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djangoproject

@djangoproject · Post #513 · 11/30/2017, 10:00 PM

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