Babelscape / token-classification updated 3 years ago

wikineural-multilingual-ner

Name: wikineural-multilingual-ner
Author: Babelscape

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

273 K

Likes

167

Commercial use: not allowed · cc-by-nc-sa-4.0 Not gated SAFETENSORS 10 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

459 K273 K

Jul 28Jul 31Aug 3Aug 6

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

indonesian-roberta-base-posp-tagger 3.1 M stanford-deidentifier-base 1.9 M bert-base-NER 1.3 M punctuate-all 708 K ner-english-fast 543 K llmlingua-2-bert-base-multilingual-cased-meetingbank 493 K

Appears in

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