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Source channel @pushgoodcloud · Post #607 · 11月30日

#Lantau#大屿山 之前购买过的,可以联系 @ljfxz 退款,直接发机场邮箱给他 剩余价值退款按照( 剩余时长*时长单价)+(剩余流量*流量单价)的形式退款 流量单价=套餐价格*0.8/套餐流量总数 时长单价=套餐价格*0.2/套餐时长总数 例如轻量套餐价格为9元,流量为80G,时长为30天。那天数单价为(0.2*9)/30,流量单价为(0.8*9)/80。 此时轻量用户还剩10天,流量还有70G,那退款为10*[(0.2*9)/30] + 70*[(0.8*9)/80] 注* 充了流量的钱也可退

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PHYGITAL+CREATIVE

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

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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PHYGITAL+CREATIVE

@phygitalcreative · Post #3158 · 2023/06/29 13:26

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

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

#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