Image Classification
Core ML
ultralytics
yolo
object-detection
instance-segmentation
pose-estimation
touchdesigner
Instructions to use mickeyvanolst/yolo-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use mickeyvanolst/yolo-coreml 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("mickeyvanolst/yolo-coreml", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
YOLO26n-seg, YOLO11n-pose, YOLO11n-cls and FastSAM-s as Core ML packages (AGPL-3.0)
1c08450 verified Download FastSAM-s.mlpackage/Data/com.apple.CoreML/model.mlmodel from mickeyvanolst/yolo-coreml: direct link, hf CLI and curl.
- Browser
- Download file 138 kB
-
https://huggingface.co/mickeyvanolst/yolo-coreml/resolve/main/FastSAM-s.mlpackage/Data/com.apple.CoreML/model.mlmodel
- Command line
-
hf download hf://mickeyvanolst/yolo-coreml/FastSAM-s.mlpackage/Data/com.apple.CoreML/model.mlmodel
-
curl -L -o model.mlmodel https://huggingface.co/mickeyvanolst/yolo-coreml/resolve/main/FastSAM-s.mlpackage/Data/com.apple.CoreML/model.mlmodel
138 kB
- Xet hash:
- 7b85e1ead905c24b20d385689d712b456866f2e52b252c4c545543471774869c
- Size of remote file:
- 138 kB
- SHA256:
- 14f52d744416a9377f3e5c58ee9eea6e20dbc7a08c9ae3ebc8664de2b35da291
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