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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.
+*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.**
 
 The colors indicate whether the <font color=#00ffff>stereotypical</font>  or the <font color=#ff00ff>less stereotypical</font> examples gets the higher score, the intensity of the color how strong the preference is.