Algorithm

Which statement correctly describes the Unigram Language Model tokenizer's training procedure?

How does weighting BPE merges by document frequency instead of raw token frequency change the resulting vocabulary?

Put the BPE training steps in the correct order, from raw corpus to final vocabulary.

Spot the error: 'BPE finds the globally optimal vocabulary by iteratively merging the most frequent pair.'