Token Classification
Transformers
Safetensors
English
Chinese
xlm-roberta
pii
pii-detection
de-identification
anonymization
redaction
legal
ner
Instructions to use libraos/veil-detect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use libraos/veil-detect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="libraos/veil-detect")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("libraos/veil-detect") model = AutoModelForTokenClassification.from_pretrained("libraos/veil-detect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download NOTICE from libraos/veil-detect: direct link, hf CLI and curl.
- Browser
- Download file 584 Bytes
-
https://huggingface.co/libraos/veil-detect/resolve/main/NOTICE
- Command line
-
hf download hf://libraos/veil-detect/NOTICE
-
curl -L -o NOTICE https://huggingface.co/libraos/veil-detect/resolve/main/NOTICE
584 Bytes
| veil-detect | |
| Copyright 2026 Libra OS | |
| This model was fine-tuned from FacebookAI/xlm-roberta-base (MIT License). | |
| Training data includes: | |
| - Nemotron-PII by NVIDIA Corporation, licensed under CC BY 4.0 | |
| (https://huggingface.co/datasets/nvidia/Nemotron-PII, | |
| https://creativecommons.org/licenses/by/4.0/). Used to train this model; no records are redistributed. | |
| - gravitee-io/pii-detection-dataset (Apache-2.0) and its upstream sources. | |
| - gretelai/synthetic_pii_finance_multilingual (Apache-2.0). | |
| - CLUENER2020 (Apache-2.0). | |
| - Text Anonymization Benchmark, TAB (MIT), train split only. | |