# Nordic Language Processing

Danish BERT is a language model optimized for Danish, excelling in the Danish ScandEval benchmark.

Icelandic masked language model trained on RoBERTa-base architecture using the fairseq framework

A Swedish RoBERTa model trained on the MC4 dataset, performance yet to be evaluated.

A BERT model fine-tuned for Danish sentiment analysis, used to detect text sentiment polarity (positive/neutral/negative)

BERT model optimized for Swedish fear sentiment analysis, capable of identifying fear/anxiety intensity in text

FinEst BERT is a trilingual model based on the bert-base architecture, specializing in Finnish, Estonian, and English processing. It outperforms multilingual BERT models while retaining cross-lingual knowledge transfer capabilities.

This is a Norwegian T5-based model trained on the Norwegian Colossal Corpus (NCC) using TPU v3-8.

BERT model for detecting sentiment polarity (positive/neutral/negative) in Danish text

A Danish BERT-based text emotion classification model that categorizes Danish text into 8 emotion categories