Language models are few-shot learners (with 30 co-authors)
3 korrents from this paper
In plain words
Larger language models can do new tasks after seeing just a few examples in plain text, with no extra training, sometimes matching systems that got thousands of examples. This reduces the need to collect huge labeled datasets for every new task. It reports results on a 175 billion parameter model tested this way, building on prior pre-training work that still required task-specific extra training.
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