wikineural-multilingual-ner
This is the model card for the EMNLP 2021 paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER. We fine-tuned a multilingual language model (mBERT) for 3 epochs on our WikiNEuRal dataset for Named Entity Recognition (NER). The resulting multilingual NER model supports the 9 languages covered by WikiNEuRal (de, en, es, fr, it, nl, pl, pt, ru), and it was trained on all 9 lang...
Params
180 M
Context
512
Downloads 30d
678 K
Likes
168
Commercial use: not allowed · cc-by-nc-sa-4.0
Not gated
SAFETENSORS
10 languages
View on Hugging Face ↗
Download history
daily snapshots · 55 days
▲ 317 K in the last 30 days (87.9%)
680 K375 K
Aug 22Sep 1Sep 11Sep 20
680 K241 K
Jul 28Aug 15Sep 2Sep 20
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.7 GB | 1.3 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- BertForTokenClassification
- Parameters
- 180 M
- Tensor type
- F32
- Context length
- 512
- Vocabulary
- 119,547
- Layers / heads
- 12 / 12
- Licence
- cc-by-nc-sa-4.0
- First seen on the Hub
- 2022-03-02
- Training datasets
- Babelscape/wikineural
- Added to our catalog
- 2026-07-28
Compare with any token-classification model