Token Classification
Transformers
TensorBoard
Safetensors
layoutlmv3
Generated from Trainer
invoice-processing
information-extraction
czech-language
document-ai
layout-aware-model
multimodal-model
synthetic-data
hybrid-data
Instructions to use TomasFAV/Layoutlmv3InvoiceCzechV012 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomasFAV/Layoutlmv3InvoiceCzechV012 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="TomasFAV/Layoutlmv3InvoiceCzechV012")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("TomasFAV/Layoutlmv3InvoiceCzechV012") model = AutoModelForTokenClassification.from_pretrained("TomasFAV/Layoutlmv3InvoiceCzechV012") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1781d77fe564177c1879aff4bc24ba697c2a9e82cb25758532acb2226693061a
- Size of remote file:
- 5.2 kB
- SHA256:
- d81677c9b7b4d082115a9caf902560f186bbe5cbb09bd1506af7c5d379b693ec
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