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
Download data/paper/book-data/trackA_dot_eq-ish_rows.dat from cloudkites/her2-reader: direct link, hf CLI and curl.
- Browser
- Download file 123 Bytes
-
https://huggingface.co/cloudkites/her2-reader/resolve/main/data/paper/book-data/trackA_dot_eq-ish_rows.dat
- Command line
-
hf download hf://cloudkites/her2-reader/data/paper/book-data/trackA_dot_eq-ish_rows.dat
-
curl -L -o trackA_dot_eq-ish_rows.dat https://huggingface.co/cloudkites/her2-reader/resolve/main/data/paper/book-data/trackA_dot_eq-ish_rows.dat
123 Bytes
| y label | |
| 1 H-optimus-0, card norm., CLS | |
| 2 ssl-vits16 final (93k) | |
| 3 D13: Midnight-12k teacher, 20k steps | |
| 4 Midnight-12k, CLS | |