Token Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
invoice-processing
information-extraction
czech-language
synthetic-data
hybrid-data
Instructions to use TomasFAV/BERTInvoiceCzechV012 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomasFAV/BERTInvoiceCzechV012 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="TomasFAV/BERTInvoiceCzechV012")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("TomasFAV/BERTInvoiceCzechV012") model = AutoModelForTokenClassification.from_pretrained("TomasFAV/BERTInvoiceCzechV012", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8319ec89d89f2f69f0d2f479a28bc53b7a915fbaf1f14fd47c5f62665292ee74
- Size of remote file:
- 5.2 kB
- SHA256:
- 73f2e4cb5cf9f21fa8ae6107273661777ccabb1eb8be367adb878fa01ba3aae6
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