Instructions to use arthrod/c5k-deberta_base-token_level-1-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use arthrod/c5k-deberta_base-token_level-1-2 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("arthrod/c5k-deberta_base-token_level-1-2") - Notebooks
- Google Colab
- Kaggle
c5k-deberta_base-token_level-1-2
Token-level GLiNER checkpoint fine-tuned for Brazilian Portuguese PII detection. Base model: microsoft/deberta-v3-base (~NoneM params).
Results
Evaluated via the scripts in gliner-onnx-benchmark on the following holdouts (Strict = exact span, Partial = overlap).
| Holdout | N | Strict F1 | Strict P | Strict R | Partial F1 |
|---|
Intended use
Brazilian Portuguese PII detection in legal, medical, and administrative text. Supports any GLiNER-compatible label set (CPF, RG, email, phone, person name, address, etc.).
Limitations
- Trained primarily on Portuguese text; English/Spanish performance is not guaranteed.
- Span boundaries depend on tokenization at inference time. See the inference rule in the repo โ never reconstruct raw text from tokens.
Citation
@misc{arthrod_gliner_ptbr_pii,
author = {arthrod},
title = {GLiNER Portuguese PII checkpoints},
year = {2026},
url = {https://huggingface.co/arthrod/c5k-deberta_base-token_level-1-2}
}
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Model tree for arthrod/c5k-deberta_base-token_level-1-2
Base model
microsoft/deberta-v3-base