Instructions to use facebook/deit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/deit-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/deit-base-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-patch16-224") model = AutoModelForImageClassification.from_pretrained("facebook/deit-base-patch16-224", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de1f97ce26553e271bf1c3a35e2d5c5deee51015e472b8d378e31c7a33d50f53
- Size of remote file:
- 347 MB
- SHA256:
- 90a7237001a4628bf3cd6c88876e2ce06c0697c310f2d4d3767c19e066fc9987
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