Instructions to use facebook/deit-small-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/deit-small-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/deit-small-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-small-patch16-224") model = AutoModelForImageClassification.from_pretrained("facebook/deit-small-patch16-224", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4181cc69047561ac35a3fae449f767f4860cf3ad1e3ad095d18eeb5ebea81d2e
- Size of remote file:
- 88.5 MB
- SHA256:
- 43160787f644b779af11e010a117a1b074edfb1bc7cfc1454d2a24f6dc7a1051
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