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Source channel @githubtrending · Post #15104 · Aug 30

#shell#alpine#alpine_linux#boot#distro#grub#installer#iso#linux#linux_distribution#liveos#netboot#netinst#netinstall#operating_systems#os#reinstall#shell_script#vps#windows You can use a powerful script to easily reinstall Linux or Windows on your server with just one command. It supports 19 popular Linux versions and all Windows versions from Vista to Windows 11, automatically downloading official ISO files and drivers. It works for switching between Linux and Windows, handles different network setups without manual IP input, and supports BIOS, EFI, and ARM servers. The script is lightweight, safe, and fetches all resources live from official sources. This saves you time and effort in system installation or reinstallation, especially on low-memory or cloud servers. You can also customize passwords, SSH keys, and ports during installation. https://github.com/bin456789/reinstall

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@phygitalcreative · Post #3136 · 06/26/2023, 01:04 AM

А вот подвезли официальный код DragGAN. Интересно насколько его работа отличается от неофициальной имплементации. В основе StyleGAN3 и StyleGAN-Human. Код #image2image

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@phygitalcreative · Post #3158 · 06/29/2023, 01:26 PM

Mixed Image Editing Playground AI выкатили редактор изображений с большинством последних достижений в этой области. #image2image#imageediting

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@githubtrending · Post #14988 · 07/23/2025, 12:00 AM

#python#deep_learning#diffusion#flax#flux#hacktoberfest#image_generation#image2image#image2video#jax#latent_diffusion_models#pytorch#score_based_generative_modeling#stable_diffusion#stable_diffusion_diffusers#text2image#text2video#video2video The Hugging Face Diffusers library is a powerful and easy-to-use tool for generating images, audio, and 3D molecular structures using advanced diffusion models. It offers ready-to-use pretrained models and flexible components like pipelines, schedulers, and model building blocks, allowing you to quickly create or customize your own diffusion-based projects. Installation is simple via pip or conda, and you can generate high-quality outputs with just a few lines of code. This library benefits you by making cutting-edge AI generation accessible, customizable, and efficient, whether you want to run models or train your own[1][2][5]. https://github.com/huggingface/diffusers