Instructions to use HorcruxNo13/beit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/beit-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/beit-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("HorcruxNo13/beit-base-patch16-224") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/beit-base-patch16-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a61c513edc8c643b393962bade57dd6bf8d8504c345e22f82286c522003d898
- Size of remote file:
- 343 MB
- SHA256:
- a05850a1d4ffcf89e5c2a9c13006eb0db48fc061b10a25157234c847a416d627
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