Instructions to use sylvain471/beit_doc_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sylvain471/beit_doc_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sylvain471/beit_doc_classification") 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("sylvain471/beit_doc_classification") model = AutoModelForImageClassification.from_pretrained("sylvain471/beit_doc_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54e9c8d08caacdbcc3bd6c218287ba8ca0c00cdaaefa3aa5c317ca30b866d99f
- Size of remote file:
- 686 MB
- SHA256:
- 43a055749e7876c3ad5198c6a3b9a25fbc6bc1d8de1f6edfc56d9117690bbc57
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