#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
#Elezioni#Romania#Presidenziali
Risultati definitivi:
Affluenza: 53,21% (+0,65 rispetto al 2024)
George #Simion (#AUR|ECR): 40,96%
Nicușor #Dan (supp. #USR-#DREPT-#PMP-#FD-#REPER-#PRA-#Verzii|EPP|RE|G/EFA): 20,99%
Crin #Antonescu (supp. #ARo|S&D|EPP): 20,07%
Victor #Ponta: 13,04%
Elena #Lasconi (#USR|RE): 2,68%
Lavinia #Șandru (#PUSL|Centro umanista populista): 0,64%
Daniel #Funeriu: 0,43%
Cristian #Terheș (#PNCR|ECR): 0,39%
Sebastian #Popescu (#PNR|Populisti): 0,28%
John Ion #Banu: 0,23%
Silviu #Predoiu (#PLAN|Centro): 0,18%
Necessario un secondo turno tra Simion e Dan.
In foto, la mappa del voto.
@OsservatorioEsteri