license: apache-2.0
library_name: gliner2
base_model: fastino/gliner2-privacy-filter-PII-multi
datasets:
- synthetic
language:
- en
- fr
- es
- de
- it
- pt
- nl
pipeline_tag: token-classification
tags:
- onnx
- pii
- ner
- privacy
- redaction
- gliner
- gliner2
- information-extraction
- span-extraction
GLiNER2-PII ONNX
This model is meant for use within the Redacta chrome extension, and this ONNX export was specifically meant for browser use, removing dependencies and preserving behavior.
GLINER2-PII ONNX is 2.75x smaller than the original GLINER2-PII with nearing performance.
Benchmark Results (SPY)
Evaluated on the SPY benchmark (Savkin et al., 2025) with exact-match span-level metrics:
| Model | Legal P | Legal R | Legal F1 | Medical P | Medical R | Medical F1 | Avg F1 |
|---|---|---|---|---|---|---|---|
| yethdev/gliner2-pii-onnx | .383 | .861 | .530 | .396 | .846 | .539 | .535 |
| fastino/gliner2-pii-v1 | .346 | .750 | .473 | .369 | .686 | .480 | .477 |
| nvidia/gliner-PII | .343 | .452 | .390 | .368 | .465 | .411 | .400 |
| urchade/gliner_multi_pii-v1 | .467 | .317 | .377 | .518 | .351 | .419 | .398 |
| openai/privacy-filter | .242 | .656 | .354 | .287 | .692 | .406 | .380 |
Setup for the yethdev/gliner2-pii-onnx row: full splits (4,197 legal questions, 4,491 medical consultations), entities materialized with faker_random_seed=42, micro-averaged exact character-level span match on the model's raw span output (no text-level deduplication). The model was queried with the labels email, id number, name, phone number, address, url, username mapped 1:1 to SPY categories, at confidence threshold 0.3; label phrasing and threshold were selected on a held-out 5% development sample. Inference ran the released model.quantized.onnx via onnxruntime (CPU), which matches the PyTorch engine's span sets on text up to 2,900 subwords with max confidence drift under 0.03.
License & attribution
Apache-2.0 - All model weights are derived from fastino/gliner2-privacy-filter-PII-multi by Fastino Labs.