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The Importance of Optimizing Pre-Training for Multilingual Data
This is work that started with UL2, a paper that was released also last year. The total amount of data being used for these models was relatively low compared to the number of parameters. This especially focused on multilingual data and more code data in a bunch of different coding languages as well. We're just zooming out a little bit in terms of when you might apply some of these different techniques to align a model to a specific domain. And I think it really comes down to the data that's available, both in quantity and relevance to a particular topic.