Token Classification
GLiNER
PyTorch
6 languages
urchade commited on
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  - it
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  library_name: gliner
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  pipeline_tag: token-classification
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+
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+
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+ # Model Card for GLiNER-multi
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+
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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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+
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+ 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`.
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+
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+ ## Links
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+
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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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+
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+ model = GLiNER.from_pretrained("urchade/gliner_multi_pii-v1")
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+
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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 [email protected]. Il a fourni son numéro de sécu 501-02-1234 pour l'enregistrement.
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+ """
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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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+
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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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+ ```
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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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+ [email protected] => email
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+ 501-02-1234 => Social Security Number
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+ ```