Image Classification
timm
ONNX
PyTorch
English
medical
histopathology
cancer-detection
binary-classification
efficientnet
int8
Eval Results (legacy)
Instructions to use AegisOSS/stage-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use AegisOSS/stage-1 with timm:
import timm model = timm.create_model("hf_hub:AegisOSS/stage-1", pretrained=True) - Notebooks
- Google Colab
- Kaggle
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| "non_cancerous": 6211, | |
| "cancer_ratio": 0.37871361408422527, | |
| "per_dataset": { | |
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| "camelyon17_jxie": 2499 | |
| } | |
| } | |
| } |