MaLA-500: Massive Language Adaptation of Large Language Models
Authors: name: Peiqin Lin, name: Shaoxiong Ji, name: Jörg Tiedemann, name: André F. T. Martins, name: Hinrich Schütze

Large language models have advanced the state of the art in natural language
processing. However, their predominant design for English or a limited set of
languages creates a substantial gap in their effectiveness for low-resource
languages. To bridge this gap, we introduce MaLA-500, a novel large language
model designed to cover an extensive range of 534 languages. To train MaLA-500,
we employ vocabulary extension and continued pretraining on LLaMA 2 with
Glot500-c. Our experiments on SIB-200 show that MaLA-500 achieves
state-of-the-art in-context learning results. We release MaLA-500 at
https://huggingface.co/MaLA-LM