glitext-pii-base

Model Card for GLiNER PII

GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.

This model has been trained by fine-tuning urchade/gliner_multi-v2.1 on the urchade/synthetic-pii-ner-mistral-v1 dataset.

This model is capable of recognizing various types of personally identifiable information (PII), including but not limited to these entity types: person, organization, phone number, address, passport number, email, credit card number, social security number, health insurance id number, date of birth, mobile phone number, bank account number, medication, cpf, driver's license number, tax identification number, medical condition, identity card number, national id number, ip address, email address, iban, credit card expiration date, username, health insurance number, registration number, student id number, insurance number, flight number, landline phone number, blood type, cvv, reservation number, digital signature, social media handle, license plate number, cnpj, postal code, passport_number, serial number, vehicle registration number, credit card brand, fax number, visa number, insurance company, identity document number, transaction number, national health insurance number, cvc, birth certificate number, train ticket number, passport expiration date, and social_security_number.

Links

• Paper: https://arxiv.org/abs/2311.08526
• Repository: https://github.com/urchade/GLiNER

from gliner import GLiNER

model = GLiNER.from_pretrained("urchade/gliner_multi_pii-v1")

text = """
Harilala Rasoanaivo, un homme d'affaires local d'Antananarivo, a enregistré une nouvelle société nommée "Rasoanaivo Enterprises" au Lot II M 92 Antohomadinika. Son numéro est le +261 32 22 345 67, et son adresse électronique est [email protected]. Il a fourni son numéro de sécu 501-02-1234 pour l'enregistrement.
"""

labels = ["work", "booking number", "personally identifiable information", "driver licence", "person", "book", "full address", "company", "actor", "character", "email", "passport number", "Social Security Number", "phone number"]
entities = model.predict_entities(text, labels)

for entity in entities:
    print(entity["text"], "=>", entity["label"])

Harilala Rasoanaivo => person
Rasoanaivo Enterprises => company
Lot II M 92 Antohomadinika => full address
+261 32 22 345 67 => phone number
[email protected] => email
501-02-1234 => Social Security Number

Source Model Repo

This model is derived from urchade/gliner_multi_pii-v1. See the upstream repository for the original safetensors weights, training data, and the full upstream model card.

ONNX Weights

ONNX weights added by SAS — converted from the upstream safetensors checkpoint.

File in this repo: model.onnx.

Using this Model with the SAS GLiText API

This repo is consumed by the SAS GLiText product. To download it onto a SAS GLiText server:

POST /v1/models/download?name=pii-base

To download and load into memory in one step:

PUT /v1/models?name=pii-base

Security Scan

Scanned with modelaudit v0.2.40 on 2026-04-27. 29/29 checks passed. Full results.