Instructions to use JWonderLand/StainNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use JWonderLand/StainNet with timm:
import timm model = timm.create_model("hf_hub:JWonderLand/StainNet", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5daac66ef37c4efdca53b9dafa07f1dd4e24d2d3be50f5ac6135cf1cbe80313
- Size of remote file:
- 86.7 MB
- SHA256:
- f9685cba98a3f208a7c25680a4b94500b3cb8f1833271a14e264c1865bc69bff
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