cordwainersmith commited on
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  1. app.py +0 -1
app.py CHANGED
@@ -49,7 +49,6 @@ MODEL_DETAILS = {
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  individuals' personal information. The model can be deployed on-premise with a
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  relatively small hardware footprint, making it suitable for organizations with
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  limited computing resources or those prioritizing local data processing.
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-
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  The model was trained on the <a href="https://huggingface.co/datasets/CordwainerSmith/GolemGuard"
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  target="_blank">GolemGuard</a> dataset, a Hebrew language dataset comprising over
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  115,000 examples of PII entities and containing both real and synthetically
 
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  individuals' personal information. The model can be deployed on-premise with a
50
  relatively small hardware footprint, making it suitable for organizations with
51
  limited computing resources or those prioritizing local data processing.
 
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  The model was trained on the <a href="https://huggingface.co/datasets/CordwainerSmith/GolemGuard"
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  target="_blank">GolemGuard</a> dataset, a Hebrew language dataset comprising over
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  115,000 examples of PII entities and containing both real and synthetically