Instructions to use facebook/deit-base-patch16-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/deit-base-patch16-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/deit-base-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-patch16-384") model = AutoModelForImageClassification.from_pretrained("facebook/deit-base-patch16-384") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea95627ab16f720f8d3d2594b3bec0064acf1d904e010c0fb4496d6edb49ebce
- Size of remote file:
- 348 MB
- SHA256:
- e0b7a93fd79a18c8dca6baca665fad2b2b1d4a3eddb8a9b57084d3db703164ad
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