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Source channel @githubtrending · Post #15365 · Dec 24

#jupyter_notebook DINOv3 offers powerful self-supervised vision models from Meta AI, like ViT up to 7B parameters and ConvNeXt, pretrained on 1.7B web or satellite images. Load them easily via PyTorch Hub, Hugging Face Transformers (v4.56+), or timm (v1.0.20+), with code examples for features, depth, detection, and segmentation. You benefit by using these top-performing, dense features without fine-tuning or labels—saving time and compute for tasks like classification, object detection, and zero-shot analysis on your images. https://github.com/facebookresearch/dinov3

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Co-Learning Center

@colearninguz · Post #12 · 12/27/2020, 07:29 AM

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Dasturlash doimiy ravishda oʻz ustida ishlash degani. Shuningdek, u toʻxtovsiz oʻrganishni ham talab etadi. Oʻrganish jarayonida kitobdan yaxshi koʻmakchi yoʻq, shunday emasmi? 🧑‍💻 “Clean Code: A Handbook of Agile Software Craftsmanship” Robert C. Martinʼning kitobi boʻlib, unda kodni tozalash, yozish va qayta tiklash boʻyicha batafsil, bosqichma-bosqich tushuntirishlar mavjud. Siz dasturiy taʼminotni ishlab chiqish loyihalarida SDLC'ning yetakchi shakllaridan biri boʻlgan Agile metodologiyasini gʻayrat bilan amalga oshira olasiz. Bundan tashqari, siz avvalgidan koʻra qatʼiyatli va intizomli dasturchi boʻlasiz. #CLC#Chitay#Coding_hazil_emas @colearninguz

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