Instructions to use microsoft/dit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/dit-base with Transformers:
# Load model directly from transformers import AutoImageProcessor, BeitForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("microsoft/dit-base") model = BeitForMaskedImageModeling.from_pretrained("microsoft/dit-base") - Notebooks
- Google Colab
- Kaggle
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README.md
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import torch
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from PIL import Image
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image = Image.open('path_to_your_document_image')
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feature_extractor = BeitFeatureExtractor.from_pretrained("microsoft/dit-base")
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model = BeitForMaskedImageModeling.from_pretrained("microsoft/dit-base")
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import torch
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from PIL import Image
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image = Image.open('path_to_your_document_image').convert('RGB')
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feature_extractor = BeitFeatureExtractor.from_pretrained("microsoft/dit-base")
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model = BeitForMaskedImageModeling.from_pretrained("microsoft/dit-base")
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