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@repo_science · Post #3771 · 12/01/2023, 11:53 PM
#python#cheatsheets Here is an amazing Python cheat sheet for you all! ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----
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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 #15000 · 07/27/2025, 12:00 PM
#markdown#android#bsd#cheatsheet#cheatsheets#command_line#console#documentation#examples#hacktoberfest#help#linux#macos#man_page#manpages#manual#osx#shell#terminal#tldr#windows The tldr-pages project offers simple, easy-to-understand help pages for command-line tools, focusing on practical examples rather than long, complex manuals. It’s great if you’re new to the command line or forget command options, as it shows the most useful commands clearly. You can access these pages through various clients or online without installing anything. This saves you time and frustration by giving quick, clear guidance on common tasks, making it easier to learn and use command-line tools effectively. Plus, you can contribute by adding or improving pages yourself. This helps you and others get fast, practical help with commands[1][4]. https://github.com/tldr-pages/tldr