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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 723a070cb3786d7da740406401d051676e57b895e514cc90c88c5ead0ec0eef2
- Size of remote file:
- 350 MB
- SHA256:
- 6c0d248fcb1b511b3d2a4dc2c6ef06af3b9a034312a49ec0ba7d38d8b4e75e2f
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