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Soumendu Pal

mlops-senz
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replied to urchade's post 1 day ago
**Release Announcement: gliner_multi_pii-v1** I am pleased to announce the release of gliner_multi_pii-v1, a model developed for recognizing a wide range of Personally Identifiable Information (PII). This model is the result of fine-tuning the urchade/gliner_multi-v2.1 on synthetic dataset (urchade/synthetic-pii-ner-mistral-v1). **Model Features:** - Capable of identifying multiple PII types including addresses, passport numbers, emails, social security numbers, and more. - Designed to assist with data protection and compliance across various domains. - Multilingual (English, French, Spanish, German, Italian, Portugese) Link: https://huggingface.co/urchade/gliner_multi_pii-v1 ```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 [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", "address", "company", "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 ```
new activity 2 days ago
urchade/gliner_multi_pii-v1:reduce FP & FN on gliner_multi_pii-v1 for fields like PAN, BAN, SSN, STATE_ID, partial detection of ADDRESS ?
liked a model 3 days ago
urchade/gliner_multi_pii-v1
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replied to urchade's post 1 day ago
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How to reduce FP & FN on gliner_multi_pii-v1 for fields like PAN, BAN, SSN, STATE_ID, partial detection of ADDRESS ,other than fine-tuning any alternative methods ?
Best efficient way to fine-tune ?
New activity in urchade/gliner_multi_pii-v1 2 days ago

reduce FP & FN on gliner_multi_pii-v1 for fields like PAN, BAN, SSN, STATE_ID, partial detection of ADDRESS ?
#7 opened 2 days ago by
mlops-senz
liked 3 models 3 days ago
liked 2 Spaces 3 months ago