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Source channel @githubtrending · Post #14988 · Jul 23

#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

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Host Testing and evaluation

@HostEvaluate · Post #863 · 04/08/2023, 08:40 AM

#Oneprovider#OneCloud#KR#ICN Host Provider: OneCloud Location: Seoul, Republic of Korea Specification: 1vCore | 1GB RAM | 30GB SSD | 1.5TB @ 1Gbps | $8 / Mo Test IP: 223.165.5.1/24 自己试吧 机器性能给人一种大树挂辣椒的感觉。上游 Ehostict 啥都不解锁。三网 SK 延迟很低但我这没速度,估计是 UDP 会被恰,也可能存粹是太挤了。 https://paste.red/p/b7cb8bcc973b