base_model: microsoft/Phi-3-mini-4k-instruct

PII Detection Model - Phi3 Mini Fine-Tuned

This repository contains a fine-tuned version of the Phi3 Mini model for detecting personally identifiable information (PII). The model has been specifically trained to recognize various PII entities in text, making it a powerful tool for tasks such as data redaction, privacy protection, and compliance with data protection regulations.

Model Overview

Model Architecture

Base Model: Phi3 Mini
Fine-Tuned For: PII detection
Framework: Hugging Face Transformers

Detected PII Entities

The model is capable of detecting the following PII entities:

Personal Information:
- firstname
- middlename
- lastname
- sex
- dob (Date of Birth)
- age
- gender
- height
- eyecolor
Contact Information:
- email
- phonenumber
- url
- username
- useragent
Address Information:
- street
- city
- state
- county
- zipcode
- country
- secondaryaddress
- buildingnumber
- ordinaldirection
Geographical Information:
- nearbygpscoordinate
Organizational Information:
- companyname
- jobtitle
- jobarea
- jobtype
Financial Information:
- accountname
- accountnumber
- creditcardnumber
- creditcardcvv
- creditcardissuer
- iban
- bic
- currency
- currencyname
- currencysymbol
- currencycode
- amount
Unique Identifiers:
- pin
- ssn
- imei (Phone IMEI)
- mac (MAC Address)
- vehiclevin (Vehicle VIN)
- vehiclevrm (Vehicle VRM)
Cryptocurrency Information:
- bitcoinaddress
- litecoinaddress
- ethereumaddress
Other Information:
- ip (IP Address)
- ipv4
- ipv6
- maskednumber
- password
- time
- ordinaldirection
- prefix

Usage

Installation

To use this model, you'll need to have the transformers library installed:

pip install transformers