Token Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
invoice-processing
information-extraction
czech-language
synthetic-data
layout-augmentation
Instructions to use TomasFAV/BERTInvoiceCzechV01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomasFAV/BERTInvoiceCzechV01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="TomasFAV/BERTInvoiceCzechV01")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("TomasFAV/BERTInvoiceCzechV01") model = AutoModelForTokenClassification.from_pretrained("TomasFAV/BERTInvoiceCzechV01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24de47abcfa57c523f75cbda576a7223094df3c969876a19ef658f87b3ca4923
- Size of remote file:
- 5.2 kB
- SHA256:
- ce863e34d54eb9d3c938202f97bd46fef2cacd7a41f15194a1873c4008d6b712
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