PIIGuard extracts personally identifiable information from English, Hindi (Devanagari), and Hinglish (code-mixed) enterprise text and returns structured JSON — built for on-prem redaction pipelines where data cannot leave the building (support transcripts, logs, KYC notes, LLM-gateway scrubbing, DPDP compliance). It handles the India-specific surface forms Western PII tools miss: Aadhaar numbers (including Devanagari digits ९८७६…), PAN codes, UPI/VPA handles, IFSC codes, Indian address formats — while deliberately ignoring lookalike traps (12-digit UTR references, order/ticket/invoice numbers, OTPs, GSTINs, employee IDs, company names). The Q4KM GGUF is 1.2GB and runs on CPU-only hardware down to a Raspberry Pi via llama.cpp/Ollama. PERSON PHONE EMAIL AADHAAR PAN ADDRESS DOB BANKACCOUNT IFSC CARD UPIID Explicitly not flagged (by design): GSTIN (public business identifier), UTR/transaction refs, OTPs, order/ticket/invoice/tracking numbers, employee IDs, company names, standalone city names, non-birth dates. Held-out test set: 1,320 examples from unseen templates and unseen PII values (train/test value pools are hash-disjoint), 200 of them PII-free. Per language F1: en 98.4 / hi…
Модальности:
Генерация текста
Области применения:
Диалог / чат Распознавание сущностей
Задача: Генерация текста
Автор: ganmoor-ai-labs
Теги: gguf, pii, pii-detection, redaction, ner, india, aadhaar, hinglish
Лайков: 4 | Загрузок: 197
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
