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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.safetensors from facebook/deit-base-distilled-patch16-384: direct link, hf CLI and curl.
- Browser
- Download file 351 MB
-
https://huggingface.co/facebook/deit-base-distilled-patch16-384/resolve/main/model.safetensors
- Command line
-
hf download hf://facebook/deit-base-distilled-patch16-384/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/facebook/deit-base-distilled-patch16-384/resolve/main/model.safetensors
351 MB
- Xet hash:
- ce80a6cf2c7cf258f5665bd47cb5b6ccde7acc57a4043c4363aed8fd95d8af5b
- Size of remote file:
- 351 MB
- SHA256:
- cdb1e860ad1dc44d319598a39e70f865609525a52197943fd68641cc1add46fd
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