Instructions to use omarelsayeed/LayoutReader90Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarelsayeed/LayoutReader90Small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="omarelsayeed/LayoutReader90Small")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("omarelsayeed/LayoutReader90Small") model = AutoModelForTokenClassification.from_pretrained("omarelsayeed/LayoutReader90Small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c26bdfcf8083f04738dead7b1381840f9bd223f442372893b42e84f7502c5f8f
- Size of remote file:
- 165 MB
- SHA256:
- 48c47c5e71547ee90f0569d0fc697349ec00d13dd58e26b4c2c4a79e9ab564e3
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