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Source channel @githubtrending · Post #14747 · May 25

#python#deep_learning#intel#machine_learning#neural_network#pytorch#quantization Intel Extension for PyTorch boosts the speed of PyTorch on Intel hardware, including both CPUs and GPUs, by using special features like AVX-512, AMX, and XMX for faster calculations[5][2][4]. It supports many popular large language models (LLMs) such as Llama, Qwen, Phi, and DeepSeek, offering optimizations for different data types and easy GPU acceleration. This means you can run advanced AI models much faster and more efficiently on your Intel computer, with simple setup and support for both ready-made and custom models. https://github.com/intel/intel-extension-for-pytorch

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@githubtrending · Post #14877 · 06/28/2025, 01:30 PM

#python#bounty#bugbounty#bypass#cheatsheet#enumeration#hacking#hacktoberfest#methodology#payload#payloads#penetration_testing#pentest#privilege_escalation#redteam#security#vulnerability#web_application Payloads All The Things is a comprehensive collection of useful payloads and bypass techniques for web application security testing and penetration testing. It offers detailed documentation for each vulnerability, including how to exploit it and ready-to-use payloads, plus files for tools like Burp Intruder. You can contribute your own payloads or improvements, making it a collaborative resource. It also links to related projects for internal network and hardware pentesting, and provides learning resources like books and videos. Using this resource helps you efficiently find and test security weaknesses in web applications, improving your pentesting effectiveness and knowledge. https://github.com/swisskyrepo/PayloadsAllTheThings