Instructions to use JcProg/PCBInspect-LeadDefect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use JcProg/PCBInspect-LeadDefect with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("JcProg/PCBInspect-LeadDefect") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download model.onnx from JcProg/PCBInspect-LeadDefect: direct link, hf CLI and curl.
- Browser
- Download file 21.8 MB
-
https://huggingface.co/JcProg/PCBInspect-LeadDefect/resolve/main/model.onnx
- Command line
-
hf download hf://JcProg/PCBInspect-LeadDefect/model.onnx
-
curl -L -o model.onnx https://huggingface.co/JcProg/PCBInspect-LeadDefect/resolve/main/model.onnx
21.8 MB
- Xet hash:
- 8ffc687237d40886d85e7b3cc2d59b86fb419f7d752a5c974786139eea781215
- Size of remote file:
- 21.8 MB
- SHA256:
- 851a12519c713e676907a5f6e65248a09b033c1c7b4f01c1c87472d6f2bd2f58
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