Instructions to use davanstrien/iiif_manuscript_vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/iiif_manuscript_vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="davanstrien/iiif_manuscript_vit") 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("davanstrien/iiif_manuscript_vit") model = AutoModelForImageClassification.from_pretrained("davanstrien/iiif_manuscript_vit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Librarian Bot: Add base_model information to model (#1)
- Librarian Bot: Add base_model information to model (e1b03c083da32e9186c26209922c2186bf31816a) Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>7574700
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update model card README.md
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davanstrien/iiif_manuscript_vit
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Training in progress, epoch 1
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initial commit
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