Instructions to use microsoft/beit-base-patch16-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/beit-base-patch16-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/beit-base-patch16-384") 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("microsoft/beit-base-patch16-384") model = AutoModelForImageClassification.from_pretrained("microsoft/beit-base-patch16-384", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from microsoft/beit-base-patch16-384: direct link, hf CLI and curl.
- Browser
- Download file 347 MB
-
https://huggingface.co/microsoft/beit-base-patch16-384/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://microsoft/beit-base-patch16-384/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/microsoft/beit-base-patch16-384/resolve/main/flax_model.msgpack
347 MB
- Xet hash:
- cd5a8de805d52ecbc26c0765fdb7042478b74f76a706f6f9e653ef95b1aeaac1
- Size of remote file:
- 347 MB
- SHA256:
- f2eb72d602d731263f828a4e19ca649828727ad7ee347c167cda84975ebbb83b
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