Instructions to use facebook/deit-base-distilled-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/deit-base-distilled-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/deit-base-distilled-patch16-224") 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("facebook/deit-base-distilled-patch16-224") model = AutoModelForImageClassification.from_pretrained("facebook/deit-base-distilled-patch16-224") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e10cd430b84994664e0eec0f19ca161153bc4d47ae68d665595e7629ab2e89c7
- Size of remote file:
- 349 MB
- SHA256:
- 5800cb485496f93b4b6e8632e358526d9279e15691cac05d31483e57dbc1390e
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