Hugging Face's logo

FelipeCasali-USP
/
lgpd_pii_identifier

Token Classification
Transformers
Portuguese
distilbert
Inference Endpoints
Model card Files Community
lgpd_pii_identifier / README.md
FelipeCasali-USP's picture
FelipeCasali-USP
Update README.md
64cafa0
preview code
|
raw
history blame
1.85 kB
metadata
language: pt
license: apache-2.0
widget:
  - text: 123.456.789-0
    example_title: CPF
  - text: '75528899000119'
    example_title: CNPJ (sem pontuação)
  - text: Nome Completo
    example_title: Felipe Casali Silva
  - text: Dados diversos
    example_title: Felipe Casali Silva, Teste, Rio de Janeiro, RJ

lgpd_pii_identifier : LGPD PII Identifier

lgpd_pii_identifier is a pre-trained NLP model to identify sensitive data in the scope of LGPD (Lei Geral de Proteção de Dados)

The goal is to have a tool to identify document numbers like CNPJ, CPF, people's names and other kind of sensitive data, allowing companies to find and anonymize data according to their businness needs, and governance rules.

Applications

Identify PII (Personal Identifiable Information) in the scope of LGPD

WIP (Add image here)

Usage

In order to use the model, you need to get the HuggingFace auth token. You can get it here.

from transformers import DistilBertModel, DistilBertTokenizer
import numpy as np
  
pred_mapper = {
    0: "cnpj",
    1: "cpf",
    2: "nome",
    3: "estado"
  }

tokenizer = DistilBertTokenizer.from_pretrained("FelipeCasali-USP/lgpd_pii_identifier")
lgpd_pii_identifier = DistilBertModel.from_pretrained("FelipeCasali-USP/lgpd_pii_identifier")

tokens = tokenizer(["String to be analized"], return_tensors="pt",
                    padding=True, truncation=True, max_length=512)
lgpd_pii_identifier_outputs = lgpd_pii_identifier(**tokens)

preds = [pred_mapper[np.argmax(pred)] for pred in lgpd_pii_identifier_outputs.logits.cpu().detach().numpy()]

Author

Paper