Token Classification
Transformers
Safetensors
Portuguese
bert
bertimbau
named-entity-recognition
ner
portuguese
pii-detection
Instructions to use fellype-dev-ai/br-access-ner-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fellype-dev-ai/br-access-ner-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fellype-dev-ai/br-access-ner-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("fellype-dev-ai/br-access-ner-v1") model = AutoModelForTokenClassification.from_pretrained("fellype-dev-ai/br-access-ner-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download label_map.json from fellype-dev-ai/br-access-ner-v1: direct link, hf CLI and curl.
- Browser
- Download file 1.89 kB
-
https://huggingface.co/fellype-dev-ai/br-access-ner-v1/resolve/main/label_map.json
- Command line
-
hf download hf://fellype-dev-ai/br-access-ner-v1/label_map.json
-
curl -L -o label_map.json https://huggingface.co/fellype-dev-ai/br-access-ner-v1/resolve/main/label_map.json
1.89 kB
| { | |
| "model_name": "neuralmind/bert-base-portuguese-cased", | |
| "entity_types": [ | |
| "CONTATO", | |
| "DADO_FINANCEIRO", | |
| "DADO_SAUDE", | |
| "DATA_NASC", | |
| "DOC_EMPRESA", | |
| "DOC_PESSOAL", | |
| "DOC_PROFISSIONAL", | |
| "ENDERECO", | |
| "ID_PROCESSUAL", | |
| "ID_VEICULO", | |
| "NOME_PESSOA", | |
| "ORG_JURIDICA", | |
| "QUASI_IDENTIFICADOR" | |
| ], | |
| "label2id": { | |
| "O": 0, | |
| "B-CONTATO": 1, | |
| "I-CONTATO": 2, | |
| "B-DADO_FINANCEIRO": 3, | |
| "I-DADO_FINANCEIRO": 4, | |
| "B-DADO_SAUDE": 5, | |
| "I-DADO_SAUDE": 6, | |
| "B-DATA_NASC": 7, | |
| "I-DATA_NASC": 8, | |
| "B-DOC_EMPRESA": 9, | |
| "I-DOC_EMPRESA": 10, | |
| "B-DOC_PESSOAL": 11, | |
| "I-DOC_PESSOAL": 12, | |
| "B-DOC_PROFISSIONAL": 13, | |
| "I-DOC_PROFISSIONAL": 14, | |
| "B-ENDERECO": 15, | |
| "I-ENDERECO": 16, | |
| "B-ID_PROCESSUAL": 17, | |
| "I-ID_PROCESSUAL": 18, | |
| "B-ID_VEICULO": 19, | |
| "I-ID_VEICULO": 20, | |
| "B-NOME_PESSOA": 21, | |
| "I-NOME_PESSOA": 22, | |
| "B-ORG_JURIDICA": 23, | |
| "I-ORG_JURIDICA": 24, | |
| "B-QUASI_IDENTIFICADOR": 25, | |
| "I-QUASI_IDENTIFICADOR": 26 | |
| }, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-CONTATO", | |
| "2": "I-CONTATO", | |
| "3": "B-DADO_FINANCEIRO", | |
| "4": "I-DADO_FINANCEIRO", | |
| "5": "B-DADO_SAUDE", | |
| "6": "I-DADO_SAUDE", | |
| "7": "B-DATA_NASC", | |
| "8": "I-DATA_NASC", | |
| "9": "B-DOC_EMPRESA", | |
| "10": "I-DOC_EMPRESA", | |
| "11": "B-DOC_PESSOAL", | |
| "12": "I-DOC_PESSOAL", | |
| "13": "B-DOC_PROFISSIONAL", | |
| "14": "I-DOC_PROFISSIONAL", | |
| "15": "B-ENDERECO", | |
| "16": "I-ENDERECO", | |
| "17": "B-ID_PROCESSUAL", | |
| "18": "I-ID_PROCESSUAL", | |
| "19": "B-ID_VEICULO", | |
| "20": "I-ID_VEICULO", | |
| "21": "B-NOME_PESSOA", | |
| "22": "I-NOME_PESSOA", | |
| "23": "B-ORG_JURIDICA", | |
| "24": "I-ORG_JURIDICA", | |
| "25": "B-QUASI_IDENTIFICADOR", | |
| "26": "I-QUASI_IDENTIFICADOR" | |
| }, | |
| "max_length": 512, | |
| "stride": 64 | |
| } |