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.dat from cloudkites/her2-reader: direct link, hf CLI and curl.
- Browser
- Download file 158 Bytes
-
https://huggingface.co/cloudkites/her2-reader/resolve/main/data/paper/book-data/trackA_dot_eq-ish.dat
- Command line
-
hf download hf://cloudkites/her2-reader/data/paper/book-data/trackA_dot_eq-ish.dat
-
curl -L -o trackA_dot_eq-ish.dat https://huggingface.co/cloudkites/her2-reader/resolve/main/data/paper/book-data/trackA_dot_eq-ish.dat
158 Bytes
| y group mean sd lo hi | |
| 1 ref 0.7646 0.1067 0.5238 0.9639 | |
| 2 s16 0.6984 0.0721 0.4253 0.9396 | |
| 3 dst 0.6899 0.1029 0.4176 0.9363 | |
| 4 ref 0.6746 0.1186 0.4111 0.9183 | |