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:
- faa9fb3c7509e765634f4c7c2272d7c14706a76b60806cfc3439b6fb6d986b15
- Size of remote file:
- 3.31 kB
- SHA256:
- 0363ce97ff371fc55e444d88359f17f16550ac0c838730a5f83d8153abc1e80e
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