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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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@libertaeragione · Post #4262 · 10/14/2024, 10:51 AM

#Elezioni#Lituania Risultati definitivi: Affluenza: 52,06% #LSDP|S&D: 19,74% #TS|EPP: 18,32% #NA|Destra radicale regionalista: 15,29% #DSVL|G/EFA: 9,42% #LRLS|RE: 7,85% #LVŽS|ECR: 7,16% #LP|RE: 4,59% #LLRA|ECR: 3,96% #NS|Estrema destra cristiana: 2,93% #LLP|Sinistra russofila euroscettica: 2,69% #TK (#DP-#LKDP-#ŽP)|Populisti|ECPM: 2,24% #LRP|Centro-sinistra conservatore: 1,93% #LŽP|Verdi di Centro europeisti: 1,71% #TTS|ESN: 1,41% #LT|Centro-destra: 0,77% In foto, la mappa del voto. @OsservatorioEsteri