Instructions to use facebook/deit-tiny-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/deit-tiny-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/deit-tiny-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-tiny-patch16-224") model = AutoModelForImageClassification.from_pretrained("facebook/deit-tiny-patch16-224") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24848d8f24c8bdd74a4e2c793570354a350158a8b8e0a3d5e756a5390b7daf0f
- Size of remote file:
- 23.2 MB
- SHA256:
- f3c4c2d90be356701bedc410769e6f1f32cdb2dd9fd7f10613eccfc772962f2e
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