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@@ -36,3 +36,25 @@ audience_classifier = pipeline("text-classification", model="Moritz-Pfeifer/Cent
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  # Perform audience classification
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  audience_result = audience_classifier("We used our liquidity tools to make funding available to banks that might need it.")
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  print("Audience Classification:", audience_result[0]['label'])
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Perform audience classification
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  audience_result = audience_classifier("We used our liquidity tools to make funding available to banks that might need it.")
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  print("Audience Classification:", audience_result[0]['label'])
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+
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+ <table>
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+ <tr>
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+ <td colspan="2" style="border-top: 1px solid #ccc; padding: 5px; text-align: left;">
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+ Please cite this model as Pfeifer, M. and Marohl, V.P. (2023) "CentralBankRoBERTa: A Fine-Tuned Large Language Model for Central Bank Communications" ADD SOURCE/LINK
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+ </td>
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+ </tr>
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+ <tr>
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+ <td style="padding: 5px;">
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+ Moritz Pfeifer<br>
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+ Institute for Economic Policy, University of Leipzig<br>
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+ 04109 Leipzig, Germany<br>
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+ <a href="mailto:[email protected]">[email protected]</a>
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+ </td>
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+ <td style="padding: 5px;">
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+ Vincent P. Marohl<br>
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+ Department of Mathematics, Columbia University<br>
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+ New York NY 10027, USA<br>
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+ <a href="mailto:[email protected]">[email protected]</a>
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+ </td>
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+ </tr>
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+ </table>