Multilingual PII Detection Model for European Languages
A state-of-the-art multilingual model for detecting Personally Identifiable Information (PII) across 26 European languages (all EU official languages). It is designed for GDPR compliance, privacy-preserving AI applications, and secure handling of sensitive data in multilingual settings. This model enables enterprises, researchers, and data protection teams to identify and safeguard PII with high accuracy (≈98%) across diverse European contexts.
from transformers import AutoTokenizer, AutoModelForTokenClassification
import torch
# Load model and tokenizer
model_name = "tabularisai/eu-pii-safeguard"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForTokenClassification.from_pretrained(model_name)
# Example text (French)
text = "Bonjour, je suis Marie Dubois, email: marie@company.fr"
# Tokenize and predict
inputs = tokenizer(text, return_tensors="pt", truncation=True)
with torch.no_grad():
outputs = model(**inputs)
predictions = torch.argmax(outputs.logits, dim=-1)
# Get predictions
tokens = tokenizer.convert_ids_to_tokens(inputs["input_ids"][0])
predicted_labels = [model.config.id2label[pred.item()] for pred in predictions[0]]
print("Detected PII:")
for token, label in zip(tokens, predicted_labels):
if label != "O":
print(f" {label}: {token}")
Transformers
Olive