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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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@githubtrending · Post #15171 · 09/27/2025, 11:30 AM

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#ruby#backup#network#nms#rancid Oxidized is a free tool that automatically backs up network device configurations from over 130 device types, replacing older tools like RANCID. It runs efficiently by adjusting how many tasks it uses based on your setup and offers a web API to manage backups and see changes. It can track who made changes using syslog and integrates with Git to show detailed version history. You can install it on many systems, configure it easily with YAML files, and use various sources and outputs for flexibility. This helps you keep your network device settings safe, organized, and easy to review or restore when needed. https://github.com/ytti/oxidized

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