  Generative Pre-trained Transformers (GPTs) have recently been scaled to
unprecedented sizes in the history of machine learning. These models, solely
trained on the language modeling objective, have been shown to exhibit
outstanding few-shot learning capabilities in a number of different tasks.
Nevertheless, aside from anecdotal experiences, little is known regarding their
multilingual capabilities, given the fact that the pre-training corpus is
almost entirely composed of English text. In this work, we investigate the
multilingual skills of GPT-3, focusing on one language that barely appears in
the pre-training corpus, Catalan, which makes the results especially
meaningful; we assume that our results may be relevant for other languages as
well. We find that the model shows an outstanding performance, particularly in
generative tasks, with predictable limitations mostly in language understanding
tasks but still with remarkable results given the zero-shot scenario. We
investigate its potential and limits in extractive question-answering and
natural language generation, as well as the effect of scale in terms of model
size.
