  This paper provides a detailed discussion of the multilingual tokenizer used
for GPT-SW3. It was trained on the Nordic Pile using the SentencePiece library
and the BPE algorithm. We outline the tokenizer's most important features and
share details on its learned vocabulary. In addition, we systematically analyze
the properties and evaluate the performance of the tokenizer with regard to the
different languages present in the data.
