Instructions to use JcProg/PCBInspect-BodyDefect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use JcProg/PCBInspect-BodyDefect 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-BodyDefect") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download model.onnx from JcProg/PCBInspect-BodyDefect: direct link, hf CLI and curl.
- Browser
- Download file 21.8 MB
-
https://huggingface.co/JcProg/PCBInspect-BodyDefect/resolve/main/model.onnx
- Command line
-
hf download hf://JcProg/PCBInspect-BodyDefect/model.onnx
-
curl -L -o model.onnx https://huggingface.co/JcProg/PCBInspect-BodyDefect/resolve/main/model.onnx
21.8 MB
- Xet hash:
- d495241abe6985200c9c6c939553a62f47ff244c341b92bad9aa8997c2287df7
- Size of remote file:
- 21.8 MB
- SHA256:
- 85912bafebeb7226e5aa86b256c5fa89d3cee5d0293360c084126bbea8b927d4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.