Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
layoutlmv3
Generated from Trainer
Eval Results (legacy)
Instructions to use oussama/layoutlmv3-finetuned-invoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oussama/layoutlmv3-finetuned-invoice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="oussama/layoutlmv3-finetuned-invoice")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("oussama/layoutlmv3-finetuned-invoice") model = AutoModelForTokenClassification.from_pretrained("oussama/layoutlmv3-finetuned-invoice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af56d837e315c56cf5f0c008fc14e2e6084b63ea7a635ed3071e345d546a1765
- Size of remote file:
- 3.38 kB
- SHA256:
- 906d3d77a7a1daa4b8b8913dd52265a86c71d76d3f3e77fe76cf3f87a6b5a5c3
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