Instructions to use omarelsayeed/LayoutReader80Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarelsayeed/LayoutReader80Small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="omarelsayeed/LayoutReader80Small")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("omarelsayeed/LayoutReader80Small") model = AutoModelForTokenClassification.from_pretrained("omarelsayeed/LayoutReader80Small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 685b229df20376ba34f6508778113780cd2da0b8ddb22bd384be1c54f4befa71
- Size of remote file:
- 165 MB
- SHA256:
- 57821482c86aad9868f79bcc363e90bf902922fc211b61f2d065e309b410c89d
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