thomasbeste/modernbert-da-ner-base-onnx-int8
By thomasbeste · ↓ 11 · ♥ 0 · Updated 2026-02-16
What's in this repo
This page lists the files in thomasbeste/modernbert-da-ner-base-onnx-int8, including model_quantized.onnx.
- 1 ONNX models (.onnx files)
- 8 files, including 5 .json, 1 .md, 1 .onnx
- Last updated 2026-02-16
ONNX files
| File | Size | Download |
|---|---|---|
| model_quantized.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
ModernBERT Danish NER (Base) — ONNX INT8
ONNX INT8 dynamically quantized version of thomasbeste/modernbert-da-ner-base.
Quantized with AVX-512 VNNI configuration for fast CPU inference.
Benchmark: DaNE Test Set
| Entity | Precision | Recall | F1 | Support |
|---|---|---|---|---|
| PER | 0.8962 | 0.9061 | 0.9011 | 181 |
| ORG | 0.6929 | 0.6299 | 0.6599 | 154 |
| LOC | 0.7500 | 0.8969 | 0.8169 | 97 |
| MISC | 0.4878 | 0.6316 | 0.5505 | 95 |
| micro avg | 0.7260 | 0.7742 | 0.7493 |
Usage
from optimum.onnxruntime import ORTModelForTokenClassification
from transformers import AutoTokenizer, pipeline
model = ORTModelForTokenClassification.from_pretrained("thomasbeste/modernbert-da-ner-base-onnx-int8")
tokenizer = AutoTokenizer.from_pretrained("thomasbeste/modernbert-da-ner-base-onnx-int8")
ner = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="simple")
results = ner("Jens Peter Hansen bor i København og arbejder hos Novo Nordisk.")
for entity in results:
print(f"{entity['word']}: {entity['entity_group']} ({entity['score']:.3f})")
Training Details
See the PyTorch model card: thomasbeste/modernbert-da-ner-base
Model info
Created: 2026-02-16
Updated: 2026-02-16
View on Hugging Face