Instructions to use SharpAI/yolo11s-coreml-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use SharpAI/yolo11s-coreml-int8 with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("SharpAI/yolo11s-coreml-int8", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
yolo11s_coreml_int8_auto
Accuracy Evaluation Results
Evaluation Dataset: coco
| Metric | Value |
|---|---|
| mAP@0.5 | 0.503 (50.3%) |
| mAP@0.5:0.95 | 0.380 (38.0%) |
| Precision | 0.440 (44.0%) |
| Recall | 0.202 (20.2%) |
| F1 Score | 0.277 (27.7%) |
| Evaluation FPS | 99.0 |
| Avg Inference Time | 10.10 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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