Instructions to use facebook/deit-base-distilled-patch16-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/deit-base-distilled-patch16-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/deit-base-distilled-patch16-384") 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-patch16-384") model = AutoModelForImageClassification.from_pretrained("facebook/deit-base-distilled-patch16-384") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e73837f127277d0370253a2f31dda2cd10fe4896672a79636df297363e1e062
- Size of remote file:
- 351 MB
- SHA256:
- dec73721e660733aa027e42bdb0e9e3ee6cbbaf05bf97965ce32d38c04f2e4e0
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