Instructions to use facebook/deit-tiny-distilled-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/deit-tiny-distilled-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/deit-tiny-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-tiny-distilled-patch16-224") model = AutoModelForImageClassification.from_pretrained("facebook/deit-tiny-distilled-patch16-224") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61c45821f14aa998bc552f805aedd13839770c980dda8f76b95b7f26f59500b8
- Size of remote file:
- 23.9 MB
- SHA256:
- 01f3055fcdbcc0943161457c307dcd5fd3af90032f5a105dbd65b2c17d760f20
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.