Token Classification
Transformers
PyTorch
TensorBoard
layoutlmv3
Generated from Trainer
Eval Results (legacy)
Instructions to use ronak1998/layoutlmv3-finetuned-invoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ronak1998/layoutlmv3-finetuned-invoice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ronak1998/layoutlmv3-finetuned-invoice")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("ronak1998/layoutlmv3-finetuned-invoice") model = AutoModelForTokenClassification.from_pretrained("ronak1998/layoutlmv3-finetuned-invoice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e72f6f4a58b8bbb8f4167e865c2d6435a39430520f2de621ea87e60848b5991
- Size of remote file:
- 504 MB
- SHA256:
- 7a2eb457ca1ebd1663818d40030174d0fc7487c27c1fd3807be752ad47eb6aff
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