Token Classification
Transformers
ONNX
Polish
German
English
bert
named-entity-recognition
ner
pii
pii-detection
pseudonymization
pseudonymisation
anonymization
privacy
gdpr
data-protection
multilingual
polish
german
english
legal
legal-nlp
Instructions to use lexedit/mbert-multilingual-legal-ner-pseudonymization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lexedit/mbert-multilingual-legal-ner-pseudonymization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="lexedit/mbert-multilingual-legal-ner-pseudonymization")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("lexedit/mbert-multilingual-legal-ner-pseudonymization") model = AutoModelForTokenClassification.from_pretrained("lexedit/mbert-multilingual-legal-ner-pseudonymization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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