---
language: no
license: cc-by-4.0
pipeline_tag: fill-mask
tags:
- norwegian
- bert
thumbnail: https://raw.githubusercontent.com/ltgoslo/NorBERT/main/Norbert.png
---

## Quickstart

**Release 1.1** (February 13, 2021)

Please check also our newer models: [NorBERT 2](https://huggingface.co/ltgoslo/norbert2) and [NorBERT 3](https://huggingface.co/ltg/norbert3-base), 
trained on a much larger corpus and with better architectures.

Download the model here:

* Cased Norwegian BERT Base: [216.zip](http://vectors.nlpl.eu/repository/20/216.zip)

More about NorBERT training corpora and training procedure: http://norlm.nlpl.eu/

Associated code: https://github.com/ltgoslo/NorBERT

Check this paper for more details:

_Andrey Kutuzov, Jeremy Barnes, Erik Velldal, Lilja Øvrelid, Stephan Oepen. [Large-Scale Contextualised Language Modelling for Norwegian](https://arxiv.org/abs/2104.06546), NoDaLiDa'21 (2021)_

NorBERT was trained as a part of NorLM, a joint initiative of the projects [EOSC-Nordic](https://www.eosc-nordic.eu/) (European Open Science Cloud) and [SANT](https://www.mn.uio.no/ifi/english/research/projects/sant/index.html) (Sentiment Analysis for Norwegian),
coordinated by the [Language Technology Group](https://www.mn.uio.no/ifi/english/research/groups/ltg/) (LTG) at the University of Oslo.

The computations were performed on resources provided by UNINETT Sigma2 - the National Infrastructure for High Performance Computing and Data Storage in Norway.

## NorBERT-3

In 2023, we released a new family of *NorBERT-3* language models for Norwegian. In general, we now recommend using these models:

- [NorBERT 3 xs](https://huggingface.co/ltg/norbert3-xs) (15M parameters)
- [NorBERT 3 small](https://huggingface.co/ltg/norbert3-small) (40M parameters)
- [NorBERT 3 base](https://huggingface.co/ltg/norbert3-base) (123M parameters)
- [NorBERT 3 large](https://huggingface.co/ltg/norbert3-large) (323M parameters)

NorBERT-3 is described in detail in this paper:
[NorBench – A Benchmark for Norwegian Language Models](https://aclanthology.org/2023.nodalida-1.61/) (Samuel et al., NoDaLiDa 2023)