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:
- 90eb11245358517c5edabafeb517ce74fd427f0697061f2a2ef102130999ef24
- Size of remote file:
- 14.6 kB
- SHA256:
- f022cc454603cf1933f0b2f55419b47e74c16e5eccd8a74e6c810757e132ec9c
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