Instructions to use microsoft/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 microsoft/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="microsoft/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("microsoft/beit-base-patch16-224-pt22k-ft22k") model = AutoModelForImageClassification.from_pretrained("microsoft/beit-base-patch16-224-pt22k-ft22k", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/beit-base-patch16-224-pt22k-ft22k: direct link, hf CLI and curl.
- Browser
- Download file 414 MB
-
https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/beit-base-patch16-224-pt22k-ft22k/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k/resolve/main/pytorch_model.bin
414 MB
- Xet hash:
- 0e96d75a660533a99d305998d3e685f42a37cf5bdf247df5fb86e5180a9f0ec8
- Size of remote file:
- 414 MB
- SHA256:
- c8caca90c227d6f47eb56be6b6ca0b10b6c28ddbfc821ac518651c574d91d4b0
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