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 # Detecting stereotypes in the GPT-2 language model using CrowS-Pairs
 
 GPT-2 is a language model which can score how likely it is that some text is a valid English sentence: not only grammaticality, but also the 'meaning' of the sentence is part of this score. CrowS-Pairs is a dataset with pairs of more and less stereotypical examples for different social groups (e.g., gender and nationality stereotypes). We sample 10 random pairs from CrowS-Pairs and show whether the stereotypical example gets a higher score ('is more likely'). If GPT-2 systematically prefers the stereotypical examples, it has probably learnt these stereotypes from the training data.
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+The colors indicate whether the $${\color{blue}stereotypical}$$ or the $${\color{pink}less stereotypical}$$ example gets the higher score.