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Source channel @githubtrending · Post #14895 · Jul 2

#python#copilot#csharp#dotnet#github#github_copilot#github_copilot_chat#github_copilot_for_azure#github_copilot_free#github_copilot_training#javascript#lab#labs#microsoft#python#sql#tutorial#tutorial_code#tutorial_exercises#visual_studio_code#vscode GitHub Copilot’s new Agent Mode is a powerful AI coding partner that goes beyond just suggesting code—it can independently write, debug, and improve your code, handle complex workflows, and even fix its own mistakes automatically. It works with multiple programming languages and integrates with popular development tools, helping you save time on repetitive tasks like testing, deployment, and refactoring. By using natural language prompts, you can guide it to complete multi-step projects, making coding faster and easier whether you’re a beginner or an expert. This course teaches you how to fully use these features, boosting your productivity and coding skills. https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming

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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

GitHub Trends

@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