Image Classification
Transformers
PyTorch
TensorBoard
English
deit
Generated from Trainer
Eval Results (legacy)
Instructions to use DunnBC22/deit-base-distilled-patch16-224-Brain_Tumors_Image_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/deit-base-distilled-patch16-224-Brain_Tumors_Image_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DunnBC22/deit-base-distilled-patch16-224-Brain_Tumors_Image_Classification") 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("DunnBC22/deit-base-distilled-patch16-224-Brain_Tumors_Image_Classification") model = AutoModelForImageClassification.from_pretrained("DunnBC22/deit-base-distilled-patch16-224-Brain_Tumors_Image_Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa24d84c62df9aca2e12954096ccffd0ca437752d3b93e98ebe255abdc661d6c
- Size of remote file:
- 343 MB
- SHA256:
- bcb12751565b98413b3b659e3e1839adab136fe7118e2190d17c40a5b0cf8890
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