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  1. YOLOv8/README.zh-CN.md at main · Pertical/YOLOv8 · GitHub

    YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite. Contribute to Pertical/YOLOv8 development by creating an account on GitHub.

  2. ultralytics/docs/en/models/yolov8.md at main - GitHub

    Ultralytics YOLO 🚀. Contribute to ultralytics/ultralytics development by creating an account on GitHub.

  3. GitHub - ultralytics/ultralytics: Ultralytics YOLO

    Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models …

  4. YOLOv8/README.zh-CN.md at main · RhineAI/YOLOv8 · GitHub

    NEW - YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite - YOLOv8/README.zh-CN.md at main · RhineAI/YOLOv8

  5. GitHub - haermosi/yolov8: YOLOv8

    Ultralytics YOLOv8, developed by Ultralytics, is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to …

  6. Neurallabware/yolo_v8: NEW - YOLOv8 in PyTorch - GitHub

    Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost …

  7. GitHub - airockchip/ultralytics_yolov8: NEW - YOLOv8 in PyTorch ...

    Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost …

  8. hero/YOLOv8: NEW - YOLOv8 in PyTorch > ONNX - GitHub

    Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost …

  9. GitHub - DataXujing/YOLOv8: :fire: Official YOLOv8模型训练和部署

    :fire: Official YOLOv8模型训练和部署. Contribute to DataXujing/YOLOv8 development by creating an account on GitHub.

  10. YOLOv8 in PyTorch > ONNX > CoreML > TFLite - GitHub

    YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite. Contribute to Pertical/YOLOv8 development by creating an account on GitHub.