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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("TomasFAV/Layoutlmv3InvoiceCzechV0") model = AutoModelForTokenClassification.from_pretrained("TomasFAV/Layoutlmv3InvoiceCzechV0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from TomasFAV/Layoutlmv3InvoiceCzechV0: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/TomasFAV/Layoutlmv3InvoiceCzechV0/resolve/main/tokenizer.json
- Command line
-
hf download hf://TomasFAV/Layoutlmv3InvoiceCzechV0/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/TomasFAV/Layoutlmv3InvoiceCzechV0/resolve/main/tokenizer.json
3.56 MB
File too large to display, you can check the raw version instead.