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Source channel @githubtrending · Post #14627 · Apr 24

#jupyter_notebook DINOv2 is a powerful AI model from Meta AI that learns to understand images without needing labeled data, using self-supervised learning. It was trained on 142 million images and creates strong visual features that work well for many tasks like image classification, depth estimation, and segmentation without extra fine-tuning. You can use its pretrained models easily with simple classifiers, saving time and effort. DINOv2 is efficient, scalable, and performs better than many other models, making it great for building versatile computer vision applications quickly and accurately. It’s open-source and ready to use with PyTorch. https://github.com/facebookresearch/dinov2

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Machinelearning

@ai_machinelearning_big_data · Post #9075 · 11/25/2025, 05:34 PM

⚡️ Релиз Flux 2 Модель получила значительный апгрейд . Теперь она учитывает до десяти референсов сразу, лучше понимает свет, материалы и оптику, аккуратнее рендерит текст и выдаёт качество до 4k. Генерации выглядят ровнее и реалистичнее, без пластикового блеска. Можно генерировать, редактировать и совмещать изображения. Веса открытые, так что при желании можно запускать локально (65 ГБ). 🟠Demo: https://playground.bfl.ai/image/generate 🟠Weights: https://huggingface.co/black-forest-labs 🟠HF: https://huggingface.co/black-forest-labs/FLUX.2-dev @ai_machinelearning_big_data #AI#Flux2#ImageGeneration#AIGraphics