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@@ -22,4 +22,16 @@ PDF processing: The 003-Main.py script processes the PDF files using OCR to extr
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  Archiving: The 004-tarballer.py script compresses the directory containing the processed files into a tarball archive.
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- Balancing: The 005-balancer.py script ensures an even distribution of PDF files across various folders.
 
 
 
 
 
 
 
 
 
 
 
 
 
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  Archiving: The 004-tarballer.py script compresses the directory containing the processed files into a tarball archive.
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+ Balancing: The 005-balancer.py script ensures an even distribution of PDF files across various folders.
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+ # Supported Tasks and Use Cases
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+ The primary use case of this dataset is to serve as training data for machine learning models that operate on text data. This may include, but is not limited to, text classification, information extraction, named entity recognition, and machine translation tasks.
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+ # Dataset Creation
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+ This dataset was generated through a multi-stage Python pipeline designed to handle the downloading, conversion, and management of large datasets.
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+ # Data Fields
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+ As the dataset contains text extracted from PDF files, the data fields primarily include the extracted text, alongside metadata about the source PDF, such as file size, number of pages, and bounding box information.