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--- |
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license: apache-2.0 |
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language: |
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- en |
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- fr |
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- de |
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- es |
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- pt |
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- it |
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library_name: gliner |
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pipeline_tag: token-classification |
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datasets: |
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- urchade/synthetic-pii-ner-mistral-v1 |
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--- |
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# Model Card for GLiNER PII |
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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. |
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This model has been trained by fine-tuning `urchade/gliner_multi-v2.1` on the `urchade/synthetic-pii-ner-mistral-v1` dataset. |
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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`. |
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## Links |
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* Paper: https://arxiv.org/abs/2311.08526 |
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* Repository: https://github.com/urchade/GLiNER |
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```python |
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from gliner import GLiNER |
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model = GLiNER.from_pretrained("urchade/gliner_multi_pii-v1") |
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text = """ |
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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 harilala.rasoanaivo@telma.mg. Il a fourni son numéro de sécu 501-02-1234 pour l'enregistrement. |
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""" |
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labels = ["work", "booking number", "personally identifiable information", "driver licence", "person", "book", "full address", "company", "actor", "character", "email", "passport number", "Social Security Number", "phone number"] |
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entities = model.predict_entities(text, labels) |
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for entity in entities: |
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print(entity["text"], "=>", entity["label"]) |
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``` |
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``` |
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Harilala Rasoanaivo => person |
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Rasoanaivo Enterprises => company |
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Lot II M 92 Antohomadinika => full address |
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+261 32 22 345 67 => phone number |
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harilala.rasoanaivo@telma.mg => email |
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501-02-1234 => Social Security Number |
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``` |
