Instructions to use SharpAI/yolo11m-coreml-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use SharpAI/yolo11m-coreml-fp16 with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("SharpAI/yolo11m-coreml-fp16") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
yolo11m_coreml_fp16_auto
Accuracy Evaluation Results
Evaluation Dataset: coco
| Metric | Value |
|---|---|
| mAP@0.5 | 0.549 (54.9%) |
| mAP@0.5:0.95 | 0.424 (42.4%) |
| Precision | 0.488 (48.8%) |
| Recall | 0.259 (25.9%) |
| F1 Score | 0.338 (33.8%) |
| Evaluation FPS | 55.1 |
| Avg Inference Time | 18.14 ms |
These metrics were computed using the Aegis AI evaluation framework on the coco dataset.
This model was automatically converted and uploaded by the Aegis AI Model Conversion Tool.
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