GLiNER-PII
GLiNER-PII is a successor to the Gretel GLiNER PII/PHI models. Built on the GLiNER bi-large base, it detects and classifies a broad range of Personally Identifiable Information (PII) and Protected Health Information (PHI) in structured and unstructured text. It is non-generative and produces span-level entity annotations with confidence scores across 55+ categories. This model was developed by NVIDIA.
Links
- Model: https://huggingface.co/nvidia/gliner-pii
- Training dataset: https://huggingface.co/datasets/nvidia/nemotron-pii
- GLiNER library: https://pypi.org/project/gliner/
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Allow for nested NER?
Allow for multi-label?
Examples