| --- |
| license: apache-2.0 |
| language: |
| - en |
| - fr |
| - de |
| - es |
| - pt |
| - it |
| library_name: glitext |
| pipeline_tag: token-classification |
| datasets: |
| - urchade/synthetic-pii-ner-mistral-v1 |
| tags: |
| - glitext |
| glitext: |
| name: pii-base |
| label: GliText PII Recognition (Balanced) |
| description: An efficient zero-shot named entity recognition model tuned for PII |
| extraction with balanced speed and accuracy. |
| recognition: true |
| classification: false |
| association: false |
| span_mode: true |
| size_gb: 1.18 |
| hf_repo: sassoftware/glitext-pii-base |
| source_url: urchade/gliner_multi_pii-v1 |
| --- |
| |
| # 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 |
|
|
| ```python |
| 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 harilala.rasoanaivo@telma.mg. 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 |
| harilala.rasoanaivo@telma.mg => email |
| 501-02-1234 => Social Security Number |
| ``` |
|
|
| ## Source Model Repo |
|
|
| This model is derived from [`urchade/gliner_multi_pii-v1`](https://huggingface.co/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](https://github.com/promptfoo/modelaudit) v0.2.40 on 2026-04-27. 29/29 checks passed. [Full results](modelaudit.json). |
|
|
|
|
| | File | Size | SHA-256 | |
| |------|------|---------| |
| | `model.onnx` | 1157.1 MB | `0772f22e05659aa5…` | |
|
|
