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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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Libreware

@libreware · Post #1262 · 03/28/2024, 03:59 PM

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⁭#Bluetooth#vulnerability allows unauthorized user to record & play audio on Bluetooth speaker via #BlueSpy Prevention section explains how you can check if your Bluetooth LE speakers/headsets are vulnerable to this attack using nRF Connect app https://www.mobile-hacker.com/2024/03/22/bluetooth-vulnerability-allows-unauthorized-user-to-record-and-play-audio-on-bluetooth-speakers/ #BlueDucky automates exploitation of Bluetooth pairing vulnerability that leads to 0-click code execution ▪️automatically scans for devices ▪️store MAC addresses of devices that are no longer visible but have enabled Bluetooth ▪️uses Rubber Ducky payloads https://www.mobile-hacker.com/2024/03/26/blueducky-automates-exploitation-of-bluetooth-pairing-vulnerability-that-leads-to-0-click-code-execution/ Demonstration of using BlueDucky to exploit 0-click Bluetooth vulnerability of unpatched Android smartphone (CVE-2023-45866) Exploit was triggered by Raspberry Pi 4 and then by Android running NetHunter https://youtu.be/GOGW7U1f2RA @androidMalware

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#bluetooth #vulnerability #bluespy #blueducky