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Update app.py

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  1. app.py +1 -1
app.py CHANGED
@@ -218,7 +218,7 @@ with GraInter:
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  <h2 style="margin-bottom: 0; font-size: 1.8em;">About</h2>
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  <strong>UGI:</strong> Uncensored General Intelligence. A measurement of the amount of uncensored/controversial information an LLM knows and is willing to tell the user. It is calculated from the average score of 5 subjects LLMs commonly refuse to talk about. The leaderboard is made of roughly 65 questions/tasks, measuring both willingness to answer and accuracy in fact-based controversial questions. I'm choosing to keep the questions private so people can't train on them and devalue the leaderboard.
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- **W/10:** Willingness/10. A more narrow subset of the UGI questions, making up a 10-point score that measures how far the model can be pushed before going against its instructions, refusing to answer, or adding an ethical disclaimer to its response.
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  <br>
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  **I/10:** Intelligence/10. A 10-point score made up of the UGI questions with the highest correlation with parameter size. This metric shows how much a model's knowledge and reasoning play a role in its UGI score.
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  <br><br>
 
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  <h2 style="margin-bottom: 0; font-size: 1.8em;">About</h2>
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  <strong>UGI:</strong> Uncensored General Intelligence. A measurement of the amount of uncensored/controversial information an LLM knows and is willing to tell the user. It is calculated from the average score of 5 subjects LLMs commonly refuse to talk about. The leaderboard is made of roughly 65 questions/tasks, measuring both willingness to answer and accuracy in fact-based controversial questions. I'm choosing to keep the questions private so people can't train on them and devalue the leaderboard.
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+ **W/10:** Willingness/10. A more narrow subset of the UGI questions, creating a 10-point score which measures how far the model can be pushed before going against its instructions, refusing to answer, or adding an ethical disclaimer to its response.
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  <br>
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  **I/10:** Intelligence/10. A 10-point score made up of the UGI questions with the highest correlation with parameter size. This metric shows how much a model's knowledge and reasoning play a role in its UGI score.
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  <br><br>