lebchen/norbert3-base-onnx
By lebchen · ↓ 2 · ♥ 0 · Updated 2026-01-26
What's in this repo
This page lists the files in lebchen/norbert3-base-onnx, including model.onnx, model_quantized.onnx.
- 2 ONNX models (.onnx files)
- 10 files, including 5 .json, 2 .onnx, 1 .md, 1 .py
- Last updated 2026-01-26
ONNX files
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
ONNX version of LtG/norbert3-base
This repository contains ONNX-converted weights for the Norwegian language model LtG/norbert3-base.
The conversion enables this state-of-the-art Norwegian model to run directly in browsers or Node.js environments using Transformers.js.
It includes both:
- Quantized (int8): Faster, smaller (default).
- Full Precision (float32): Higher theoretical accuracy.
Usage (Node.js/Web)
First, install the library:
npm install @huggingface/transformers
Option 1: Use Quantized Model (Recommended)
This is the default behavior. It loads model_quantized.onnx (approx. 4x smaller, faster inference).
import { pipeline } from '@huggingface/transformers';
// Loads the model (automatically selects the quantized version)
const embedder = await pipeline(
'feature-extraction',
'lebchen/norbert3-base-onnx',
{ device: 'auto' }
);
const sentences = [
"Dette er en setning på norsk.",
"Norbert er en språkmodell fra UiO."
];
// Norbert generally benefits from mean pooling for sentence representations
const output = await embedder(sentences, { pooling: 'mean', normalize: true });
console.log(output.tolist());
Option 2: Use Full Precision Model
To load the uncompressed model.onnx, explicitly set quantized: false.
const embedder = await pipeline(
'feature-extraction',
'lebchen/norbert3-base-onnx',
{
device: 'auto',
quantized: false
}
);
Credits & Attribution
The original model (NorBERT 3) was developed by the Language Technology Group (LTG) at the University of Oslo.
Original Repository: LtG/norbert3-base
Paper/Citation: Please refer to the original model card for proper citation if you use this in academic work.
This distribution is converted to ONNX for compatibility reasons and maintains the original Apache 2.0 license.
Model info
Created: 2026-01-26
Updated: 2026-01-26
View on Hugging Face