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@@ -56,7 +56,7 @@ unfiltered content from the internet, which is far from neutral. As the openAI t
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  > that require the generated text to be true.
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  >
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  > Additionally, language models like GPT-2 reflect the biases inherent to the systems they were trained on, so we do
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- > not recommend that they be deployed into systems that interact with humans > unless the deployers first carry out a
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  > study of biases relevant to the intended use-case. We found no statistically significant difference in gender, race,
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  > and religious bias probes between 774M and 1.5B, implying all versions of GPT-2 should be approached with similar
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  > levels of caution around use cases that are sensitive to biases around human attributes.
 
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  > that require the generated text to be true.
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  >
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  > Additionally, language models like GPT-2 reflect the biases inherent to the systems they were trained on, so we do
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+ > not recommend that they be deployed into systems that interact with humans unless the deployers first carry out a
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  > study of biases relevant to the intended use-case. We found no statistically significant difference in gender, race,
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  > and religious bias probes between 774M and 1.5B, implying all versions of GPT-2 should be approached with similar
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  > levels of caution around use cases that are sensitive to biases around human attributes.