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/paper-data/jepa_trade_b.dat from cloudkites/her2-reader: direct link, hf CLI and curl.
- Browser
- Download file 90 Bytes
-
https://huggingface.co/cloudkites/her2-reader/resolve/main/data/paper/paper-data/jepa_trade_b.dat
- Command line
-
hf download hf://cloudkites/her2-reader/data/paper/paper-data/jepa_trade_b.dat
-
curl -L -o jepa_trade_b.dat https://huggingface.co/cloudkites/her2-reader/resolve/main/data/paper/paper-data/jepa_trade_b.dat
90 Bytes
| dyy dty label | |
| 0.0100 0.0110 {B average (2 seeds)} | |
| 0.0030 0.0070 {} | |
| -0.0080 0.0090 {B 25k} | |