gliner_multi_pii-v1-tuned-2048

Entity Types Classification

Personal Information

• Date of birth
• Age
• Gender
• Last name
• Occupation
• Education level
• Phone number
• Email
• Street address
• City
• Country
• Postcode
• User name
• Password
• Tax ID
• License plate
• CVV
• Bank routing number
• Account number
• SWIFT BIC
• Biometric identifier
• Device identifier
• Location

Financial Information

• Account number
• Bank routing number
• SWIFT BIC
• CVV
• Tax ID
• API key

Health and Medical Information

• Blood type
• Biometric identifier
• Organ
• Diseases symptom
• Diagnostics
• Preventive medicine
• Treatment
• Surgery
• Drug chemical
• Medical device technique
• Personal care

Online and Web-related Information

• URL
• IP address
• Email
• User name
• API key

Professional Information

• Occupation
• Skill
• Organization
• Company name

Location Information

• City
• Country
• Postcode
• Street address
• Location

Time-Related Information

• Date
• Date time

Miscellaneous

• Event
• Miscellaneous

Product and Goods Information

• Product
• Quantity
• Food drink
• Transportation

Identifiers

• Device identifier
• Biometric identifier
• User name
• Email
• Phone number
• URL
• License plate

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.

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