Instructions to use HorcruxNo13/beit-base-patch16-224-pt22k-ft22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/beit-base-patch16-224-pt22k-ft22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/beit-base-patch16-224-pt22k-ft22k") 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-pt22k-ft22k") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/beit-base-patch16-224-pt22k-ft22k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c59a5b3c33527f0e245ce4cbf3b5d198f9c31e14c3384645cf62825381fa78f
- Size of remote file:
- 410 MB
- SHA256:
- 526537a62ac4bd96e860a8a2d1fabda9201082a5bee7a6722f2ccaaf911ab76e
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