Token Classification
Transformers
Safetensors
PyTorch
Italian
deberta-v2
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
italian
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-Italian-mSuperClinical-Large-279M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-Italian-mSuperClinical-Large-279M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-Italian-mSuperClinical-Large-279M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-Italian-mSuperClinical-Large-279M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-Italian-mSuperClinical-Large-279M-v1") - Notebooks
- Google Colab
- Kaggle
Upload Italian PII detection model OpenMed-PII-Italian-mSuperClinical-Large-279M-v1
5463580 verified - Xet hash:
- ea160564e5ab34f7d61c1b68e2e9e63cc3d28995d3bf5ebc863dc6f2d8bc5686
- Size of remote file:
- 16.4 MB
- SHA256:
- d5249d92f8d658ed3d19f52a5885b7abbf7f82a90cc18a2b6c7166af54a884f6
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