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pii-ner-model
freyavoice/pii-ner-model
pii-ner-model is a token classification model from freyavoice. Use it when you need labels on individual words, such as names. It is set up for onnx. The card lists the license as mit.
Dynamic-INT8 ONNX export of akdeniz27/bert-base-turkish-cased-ner (BERTurk, MIT). It detects free-text PII — names and addresses — that a deterministic regex masker can't catch, and runs in-process via onnxruntime (no…
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Repo size
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.onnx111 MB · 99%
At a glance
- Task
- Token Classification
- Library
- onnx
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jun 19, 2026
- Updated
- Jun 19, 2026
- SHA
- e4010ec0
Base models
Model card
From the Hugging Face model README
pii-ner-model
Dynamic-INT8 ONNX export of akdeniz27/bert-base-turkish-cased-ner
(BERTurk, MIT). It detects free-text PII — names and addresses — that a deterministic
regex masker can't catch, and runs in-process via onnxruntime (no torch).
Freya's voice agent loads it for freeform-PII redaction (src/privacy/ner.py,
LocalPiiDetector); the agent image fetches this repo at build into PII_NER_MODEL_DIR.
NER is optional + fail-open and gated per-agent by privacy_config.mask_pii.
Files
| file | what |
|---|---|
model.int8.onnx | dynamic-INT8-quantized BERTurk token-classification model (~106 MB) |
tokenizer.json | Rust-tokenizer config for the onnxruntime path |
config.json | id2label map for decode |
export_model.py | the offline recipe that produced the artifacts (not used at runtime) |
Labels
7-class BIO: O, B-PER/I-PER, B-ORG/I-ORG, B-LOC/I-LOC. Downstream mapping:
PER -> NAME, LOC -> ADDRESS; ORG is dropped.
Quality
Validated on Turkish: names F1 ~1.00 (cased) / ~0.93–0.95 (ASR-style lowercase). INT8 is
effectively lossless vs fp32 on cased text. Addresses (LOC) are weaker on lowercase ASR text.
Regenerating
Needs torch + optimum[onnxruntime] (not runtime deps):
pip install torch --index-url https://download.pytorch.org/whl/cpu
pip install "optimum[onnxruntime]" transformers
python export_model.py --model akdeniz27/bert-base-turkish-cased-ner --out /tmp/pii-ner
# then copy model_quantized.onnx -> model.int8.onnx, plus tokenizer.json + config.json
License
MIT — same as the base model. See LICENSE. Base model: akdeniz27/bert-base-turkish-cased-ner.
- Task
- Token Classification
- Library
- onnx
- Type
- bert
- License
- mit
- Languages
- tr
- Created
- Jun 19, 2026
- Updated
- Jun 19, 2026