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:
- bb633da082121a8c61f4621527fbf9224980813c32897468f056a8ff416fcc21
- Size of remote file:
- 343 MB
- SHA256:
- da9757c9d424a3641ac6eac9208b51523ae55b0b924abdf8b9d1e8436171fe6a
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