Image Feature Extraction
timm
Safetensors
pathology
histopathology
her2
breast-cancer
h-and-e
vision-transformer
multiple-instance-learning
Instructions to use cloudkites/her2-reader with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use cloudkites/her2-reader with timm:
import timm model = timm.create_model("hf-hub:cloudkites/her2-reader", pretrained=True) - Notebooks
- Google Colab
- Kaggle
File size: 374 Bytes
4367928 | 1 2 3 4 5 6 7 8 9 | y ty sd params label own
0 0.5890 0.0160 22 {DINOv2-S, natural images (22M)} 0
1 0.6380 0.0220 26 {ResNet-50, ImageNet (26M)} 0
2 0.7270 0.0290 1100 {Midnight-12k, ViT-g/14 (1.1B)} 0
3 0.7490 0.0270 86 {Hibou-B, ViT-B/14 (86M)} 0
4 0.8050 0.0200 1100 {H-optimus-0, ViT-g/14 (1.1B)} 0
5 0.8110 0.0140 86 {Phikon, ViT-B/16 (86M)} 0
6 0.8120 0.0150 22 {Ours, ViT-S/16 (22M)} 1
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