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: 508 Bytes
b711e1a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | dyy dty cls label
-0.0160 0.0270 s {M6.D (2 seeds)}
-0.0220 0.0260 s {}
0.0100 0.0210 s {v5}
-0.0100 0.0360 s {M5.G 25k (3 seeds)}
-0.0060 0.0300 s {}
-0.0080 0.0330 s {}
-0.0140 0.0500 r2 {M5.G 25k, round 2}
-0.0090 -0.0060 s {augmented student}
-0.0170 0.0140 v {LR 3e-5}
-0.0390 0.0200 v {2,000 steps (2 seeds)}
-0.0410 0.0190 v {}
0.0100 0.0110 b {B average (2 seeds)}
0.0030 0.0070 b {}
-0.0080 0.0090 b {B 25k}
-0.0500 -0.0160 bv {B, 2,000 steps (2 seeds)}
-0.0360 -0.0170 bv {}
0.0300 0.0300 s {100k}
|