PHYGITAL+CREATIVE
@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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Source channel @githubtrending · Post #14777 · Jun 3
#other#applications#coderquad#college#fulltime#hacktoberfest#jobs#newgrad#position#posting#university This resource is a regularly updated list of entry-level jobs for new graduates in software, tech, computer science, product management, and quantitative roles for 2024 and 2025, organized by Coder Quad and Simplify[1][2][4]. It features a wide range of open positions from top companies, sorted by category like software engineering, data science, AI, quantitative finance, and hardware engineering. The list is easy to browse, with direct links to apply for each job, and is updated daily so you always see the latest opportunities. You can also use tools like Simplify’s browser extension to autofill job applications and get email alerts for new roles, saving you time and effort. This helps you quickly find and apply for jobs that match your skills and interests, making your job search much easier and more efficient[1][2][4]. https://github.com/SimplifyJobs/New-Grad-Positions
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PHYGITAL+CREATIVE
@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