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@@ -66,7 +66,7 @@ sentinement_result = agent_classifier("The early effects of our policy tightenin
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  print("Sentiment:", sentinement_result[0]['label'])
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  ```
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- <table class="clearfix">>
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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". <em>Journal of Finance and Data Science </em> (forthcoming) <a href="https://doi.org/10.1016/j.jfds.2023.100114">https://doi.org/10.1016/j.jfds.2023.100114</a> </td>
 
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  print("Sentiment:", sentinement_result[0]['label'])
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  ```
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+ <table class="clearfix">
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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". <em>Journal of Finance and Data Science </em> (forthcoming) <a href="https://doi.org/10.1016/j.jfds.2023.100114">https://doi.org/10.1016/j.jfds.2023.100114</a> </td>