Token Classification
Transformers
Safetensors
layoutlmv3
Generated from Trainer
Eval Results (legacy)
Instructions to use Abinaya/layoutlmv3-finetuned-DocLayNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abinaya/layoutlmv3-finetuned-DocLayNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Abinaya/layoutlmv3-finetuned-DocLayNet")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Abinaya/layoutlmv3-finetuned-DocLayNet") model = AutoModelForTokenClassification.from_pretrained("Abinaya/layoutlmv3-finetuned-DocLayNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0fa2f0414df4175d89fc68b8167d014607409f78e5bcc60d7be8d5b629ee3d71
- Size of remote file:
- 5.24 kB
- SHA256:
- 043360ddf9c94b8397d92de1f1c8fd7a281508f2e2242a598c311d19d28162e3
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