atalaydenknalbant

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Yolov13

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This Pull Request significantly enhances the model card for YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception.

Key improvements include:

• Metadata: Added license: apache-2.0, pipeline_tag: object-detection, and library_name: ultralytics. These additions improve discoverability on the Hugging Face Hub (https://huggingface.co/models?pipeline_tag=object-detection) and enable the automated "how to use" code snippet, as evidenced by the model's explicit compatibility with the ultralytics library in the GitHub README.
• Comprehensive Content: Integrated extensive details from the official GitHub README (https://github.com/iMoonLab/yolov13), including:
  • The full paper abstract.
  • A "Updates" section showing project development history.
  • A detailed "Technical Briefing" explaining the model's innovations (HyperACE, FullPAD, DS-based Blocks).
  • "Main Results" with quantitative benchmarks (MS COCO table) and "Visualizations" (images with absolute GitHub URLs).
  • A comprehensive "Quick Start" guide with practical code snippets for installation, validation, training, prediction, and export.
  • Links to "Related Projects".
• Enhanced Links: Explicitly linked to the Hugging Face paper page (https://huggingface.co/papers/2506.17733), arXiv preprint, the GitHub repository, and the Hugging Face Spaces demo (https://huggingface.co/spaces/atalaydenknalbant/Yolov13) for easy access to all relevant resources.
• Structure and Clarity: The content is reorganized for better readability, starting with the paper title, key links, and abstract, followed by technical details and usage examples.

These updates provide a much richer, more informative, and user-friendly experience for anyone exploring the YOLOv13 model on the Hugging Face Hub.