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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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Crypto M - Crypto News

@CryptoM · Post #64625 · 04/09/2026, 11:54 AM

🚀 Independent Miner Achieves Rare Bitcoin Block Discovery An independent Bitcoin miner achieved a rare feat by successfully mining a Bitcoin block with a very low probability. According to BlockBeats, the miner used CKpool's solo mining software to mine block number 944,306, earning a total of 3.128 Bitcoin. Data from block explorer Mempool indicates that the miner received a block subsidy of 3.125 Bitcoin and transaction fees amounting to 0.003 Bitcoin. CKpool developer Con Kolivas noted on the X platform that the miner accomplished this with just 70TH of computing power. The probability of a miner of this scale discovering a block daily is approximately one in 100,000, with an average occurrence of once every 300 years. #Bitcoin#mining#CKpool#blockchain#rarefeat#blockdiscovery#cryptocurrency#soloMining#Mempool#transactionfees#ConKolivas#BTC