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Norbert

Developed by ltg
NorBERT is a BERT model optimized for Norwegian, developed by the Language Technology Group at the University of Oslo. It is part of the NorLM initiative, aiming to provide high-quality language models for Norwegian.
Large Language Model Other#Norwegian BERT#Multi-size models#Large-scale corpus training
Downloads 199
Release Time : 3/2/2022

Model Overview

NorBERT is a Norwegian pre-trained language model based on the BERT architecture, suitable for various natural language processing tasks such as text classification, named entity recognition, and question-answering systems.

Model Features

Norwegian optimization
Specifically trained and optimized for Norwegian, providing more accurate language understanding capabilities.
Multi-version support
Offers multiple versions (NorBERT, NorBERT 2, NorBERT 3) to meet different scale and performance needs.
High-performance computing support
Supported by computational resources from the Norwegian national high-performance computing and data storage infrastructure, UNINETT Sigma2.

Model Capabilities

Text filling
Language understanding
Text classification
Named entity recognition
Question-answering systems

Use Cases

Natural language processing
Text classification
Used for classification tasks in Norwegian text, such as sentiment analysis or topic classification.
Named entity recognition
Identifies named entities in Norwegian text, such as person names, place names, and organization names.
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