| Our largest model with 7.5 billion parameters | |
| sets new state of the art in few-shot learning in more than 20 representative languages, outperforming GPT-3 of comparable size | |
| in multilingual commonsense reasoning (with +7.4% absolute accuracy improvement in 0-shot settings and +9.4% in 4-shot settings) | |
| and natural language inference (+5.4% in each of 0-shot and 4-shot settings). |