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 flax_model.msgpack from microsoft/beit-base-patch16-224-pt22k-ft22k: direct link, hf CLI and curl.
- Browser
- Download file 410 MB
-
https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://microsoft/beit-base-patch16-224-pt22k-ft22k/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k/resolve/main/flax_model.msgpack
410 MB
- Xet hash:
- d7e84f19951b42e59749456ee8e92cddd0991cc9139001e564952e17c9da7128
- Size of remote file:
- 410 MB
- SHA256:
- 84ce2bd9f3a18b4eb8a4b3f365e958f9dee83008801ded8c26c9f21913370768
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