Token Classification
Transformers
Safetensors
PyTorch
Dutch
roberta
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
dutch
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-Dutch-SuperMedical-Large-355M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-Dutch-SuperMedical-Large-355M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-Dutch-SuperMedical-Large-355M-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-Dutch-SuperMedical-Large-355M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-Dutch-SuperMedical-Large-355M-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download classification_report.txt from OpenMed/OpenMed-PII-Dutch-SuperMedical-Large-355M-v1: direct link, hf CLI and curl.
- Browser
- Download file 1.21 kB
-
https://huggingface.co/OpenMed/OpenMed-PII-Dutch-SuperMedical-Large-355M-v1/resolve/main/classification_report.txt
- Command line
-
hf download hf://OpenMed/OpenMed-PII-Dutch-SuperMedical-Large-355M-v1/classification_report.txt
-
curl -L -o classification_report.txt https://huggingface.co/OpenMed/OpenMed-PII-Dutch-SuperMedical-Large-355M-v1/resolve/main/classification_report.txt
1.21 kB
| Classification Report for Dutch PII Detection | |
| Model: FacebookAI/roberta-large | |
| ============================================================ | |
| precision recall f1-score support | |
| BANKACCOUNT 0.79 0.79 0.79 136 | |
| BUILDINGNUMBER 0.90 0.93 0.92 111 | |
| CITY 0.93 0.96 0.94 334 | |
| CREDITCARD 0.81 0.86 0.84 86 | |
| DATEOFBIRTH 0.88 0.85 0.86 138 | |
| EMAIL 1.00 1.00 1.00 347 | |
| FIRSTNAME 0.81 0.89 0.85 460 | |
| LASTNAME 0.81 0.72 0.76 354 | |
| MASKEDNUMBER 0.93 0.97 0.95 77 | |
| PASSWORD 1.00 0.99 0.99 94 | |
| PHONE 1.00 1.00 1.00 230 | |
| SSN 0.97 1.00 0.99 338 | |
| STREET 0.93 0.90 0.92 123 | |
| USERNAME 0.99 0.98 0.98 367 | |
| ZIPCODE 0.96 0.97 0.96 193 | |
| micro avg 0.91 0.92 0.92 3388 | |
| macro avg 0.91 0.92 0.92 3388 | |
| weighted avg 0.91 0.92 0.92 3388 | |