  In Korean ancient documents, there is no spacing or punctuation, and they are
written in classical Chinese characters. This makes it challenging for modern
individuals and translation models to accurately interpret and translate them.
While China has models predicting punctuation and spacing, applying them
directly to Korean texts is problematic due to data differences. Therefore, we
developed the first models which predict punctuation and spacing for Korean
historical texts and evaluated their performance. Our punctuation restoration
model achieved an F1 score of 0.84, and Spacing model achieved a score of 0.96.
It has the advantage of enabling inference on low-performance GPUs with less
VRAM while maintaining quite high accuracy.
