Feature Extraction
timm
PyTorch
Safetensors
image-classification
biology
cancer
owkin
histology
Eval Results (legacy)
Instructions to use 1aurent/vit_base_patch16_224.owkin_pancancer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use 1aurent/vit_base_patch16_224.owkin_pancancer with timm:
import timm model = timm.create_model("hf_hub:1aurent/vit_base_patch16_224.owkin_pancancer", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69904170118d427ade2cae406f7afab2160c11c54e71c1357fb9031406208e02
- Size of remote file:
- 343 MB
- SHA256:
- 24b3406cdb8b655af52bc7f7d40469ddd89cce9f461d92e8f668c59d9946ca3c
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