riidact/ner-multilingual

Riidact NER — multilingual names & places

Token-classification model (PER / LOC / ORG) powering Riidact's on-device name detection. Runs in the browser via transformers.js + ONNX Runtime; the quantized weights (onnx/model_quantized.onnx, ~178 MB) are what ships.

License

These fine-tuned weights are released under CC-BY-NC-4.0: free to use, share, and adapt for non-commercial purposes, with attribution. For commercial use, contact Riidact.

The MIT-licensed base model (numind/NuNER-multilingual-v0.1) is unaffected and remains available under its own terms — see the NOTICE below. The non-commercial terms apply to this fine-tune, not to the underlying base.

Coverage

Fine-tuned on 103 languages; 88 are certified by a two-tier benchmark: realistic-sentence recall with a zero-false-positive corpus (72 languages), plus held-out WikiANN validation at PER F1 ≥ 0.80 (84 languages).

Lineage

• Backbone: numind/NuNER-multilingual-v0.1 (MIT)
• Training data: WikiANN (Wikipedia-derived, PAN-X annotations), 501k sentences across 103 languages, plus a small synthetic supplement of conversational name shapes (honorific patterns) that Wikipedia-derived data lacks.

Recommended inference floors

Span mean confidence, per entity: PER ≥ 0.55, LOC ≥ 0.9 (precision-first; calibrated against the benchmark corpus above).

NOTICE

This model is a derivative of numind/NuNER-multilingual-v0.1, licensed under the MIT License:

MIT License

Copyright (c) NuMind

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The MIT terms cover the base model. The additional non-commercial terms (CC-BY-NC-4.0) apply to the fine-tuning contribution in these weights.