Language Models are Unsupervised Multitask Learners
The capacity of the language model is essential to the success of zero-shot task transfer and in-creasing it improves performance in a log-linear fashion across tasks. Our largest model, GPT-2, is a 1.5B parameter Transformer that achieves state of the art results on 7 out of 8 tested lan-guage modeling datasets in a zero-shot setting
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Language Models are Unsupervised Multitask Learners
d4mucfpksywv.cloudfront.netthe promise of language models to perform specific tasks, such as commonsense reasoning (Schwartz et al.,2017) and sentiment analysis (Radford et al.,2017). In this paper, we connect these two lines of work and con-tinue the trend of more general methods of transfer. We demonstrate language models can perform down-stream
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