Image Classification
Transformers
TensorBoard
Safetensors
deit
Generated from Trainer
Eval Results (legacy)
Instructions to use BilalMuftuoglu/deit-base-distilled-patch16-224-55-fold5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BilalMuftuoglu/deit-base-distilled-patch16-224-55-fold5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="BilalMuftuoglu/deit-base-distilled-patch16-224-55-fold5") 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("BilalMuftuoglu/deit-base-distilled-patch16-224-55-fold5") model = AutoModelForImageClassification.from_pretrained("BilalMuftuoglu/deit-base-distilled-patch16-224-55-fold5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9535f2fecd539eb99f07459fc79a6327e6472788cebeb570981f84917745e363
- Size of remote file:
- 5.18 kB
- SHA256:
- 2bb4fa38713918d90cfdafc9941fac5ba4fcddd0589b6e891b5b671ad71a388c
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