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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 #15412 · 01/14/2026, 04:30 PM

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#jinja#ansible#ansible_collection#collection#devsec#hacktoberfest#hardening#linux#mysql_hardening#nginx#nginx_hardening#os_hardening#playbook#protection#role#ssh_hardening#sysctl devsec.hardening is an Ansible collection that battle-tests security hardening for Linux (CentOS, AlmaLinux, Rocky, Debian, Ubuntu, etc.), MySQL, Nginx, and SSH, matching DevSec Inspec baselines. Install via `ansible-galaxy collection install devsec.hardening` and apply roles like os_hardening easily. It saves you time by automating secure configs across servers, cuts manual work, boosts compliance, and shrinks attack surfaces for safer systems. https://github.com/dev-sec/ansible-collection-hardening

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#jinja #ansible #ansible_collection #collection #devsec #hacktoberfest #hardening #linux #mysql_hardening #nginx #nginx_hardening #os_hardening #playbook #protection #role #ssh_hardening #sysctl