Instructions to use omarelsayeed/LayoutReader85Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarelsayeed/LayoutReader85Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="omarelsayeed/LayoutReader85Large")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("omarelsayeed/LayoutReader85Large") model = AutoModelForTokenClassification.from_pretrained("omarelsayeed/LayoutReader85Large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72dabd42b411d914229262dcc1e414a0d9e6e752dd2c0a14562efef1f1918051
- Size of remote file:
- 1.42 GB
- SHA256:
- cf9e399d300f5d74049bda7d40980056583affc0aae182cf5b9d5d783cbbfdf7
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