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")# pip install -U transformers accelerate # 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
Download pytorch_model.bin from HorcruxNo13/beit-base-patch16-224-pt22k-ft22k: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/HorcruxNo13/beit-base-patch16-224-pt22k-ft22k/resolve/b5ca25862d1180599aaca3272eb147e22c885436/pytorch_model.bin
- Command line
-
hf download hf://HorcruxNo13/beit-base-patch16-224-pt22k-ft22k@b5ca25862d1180599aaca3272eb147e22c885436/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HorcruxNo13/beit-base-patch16-224-pt22k-ft22k/resolve/b5ca25862d1180599aaca3272eb147e22c885436/pytorch_model.bin
343 MB
- Xet hash:
- aedb0f24cfe24b8af25cefd518e76c5d45cf8a4bb9038e7098485eeee6fb37d0
- Size of remote file:
- 343 MB
- SHA256:
- e7c69223fbf1aa51f9cae6ba838b55372664a6a9d2e3a9544f29964e277f23f0
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