Token Classification
Transformers
TensorBoard
Safetensors
layoutlmv3
Generated from Trainer
invoice-processing
information-extraction
czech-language
document-ai
layout-aware-model
multimodal-model
synthetic-data
Instructions to use TomasFAV/Layoutlmv3InvoiceCzechV0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomasFAV/Layoutlmv3InvoiceCzechV0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="TomasFAV/Layoutlmv3InvoiceCzechV0")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("TomasFAV/Layoutlmv3InvoiceCzechV0") model = AutoModelForTokenClassification.from_pretrained("TomasFAV/Layoutlmv3InvoiceCzechV0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69cbf2b21ddd7745d45a43a87d7e5143a0e924cf7a13cabbddb808548244b9a4
- Size of remote file:
- 5.2 kB
- SHA256:
- 20b3419a9e7ed4f1eb37f56a1dba2475a6f79bda623b7014f0d9ad03dfd7f80a
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