Update README.md

README.md

@@ -9,4 +9,43 @@ language:
 - it
 library_name: gliner
 pipeline_tag: token-classification
----
+datasets:
+- urchade/synthetic-pii-ner-mistral-v1
+---
+
+
+# Model Card for GLiNER-multi
+
+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 version has been ot recognize and classify **Personally Identifiable Information** (PII) within text. The training dataset has been generated using `mistralai/Mistral-7B-Instruct-v0.2`.
+
+## 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
+```