Image Classification
Transformers
TensorBoard
Safetensors
vit
feature-extraction
biology
cancer
owkin
histology
Eval Results (legacy)
Instructions to use 1aurent/phikon-distil-vit-tiny-patch16-224-kather2016 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 1aurent/phikon-distil-vit-tiny-patch16-224-kather2016 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="1aurent/phikon-distil-vit-tiny-patch16-224-kather2016") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("1aurent/phikon-distil-vit-tiny-patch16-224-kather2016") model = AutoModelForImageClassification.from_pretrained("1aurent/phikon-distil-vit-tiny-patch16-224-kather2016") - Notebooks
- Google Colab
- Kaggle
Ctrl+K