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@@ -43,7 +43,8 @@ The dataset is focussed on Indian factual content for pre-training LLMs where In
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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  Total number of rows: 200820 \
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- It has approximately **1.54** billion tokens for all languages with almost similar number of tokens for each language when tokenized
 
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  with our Indic tokenizer we created which can be found in our model repository [Pragna-1b](https://huggingface.co/soketlabs/pragna-1b).
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  Here are token counts for each language:
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  - English: 196.2 millions
@@ -61,6 +62,7 @@ The title is in english and descriptions in different languages is represented b
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  Each description column in different languages is a list of sentences/multiple sentences and can be concatenated to get cleaned article decription.
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  Each row is of the format:
 
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  {'id': '1',
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  'url': 'https://simple.wikipedia.org/sample_article',
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  'title': 'Sample article',
 
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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  Total number of rows: 200820 \
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+ It has approximately **1.54** billion tokens for all languages. The ratio for number of tokens for each language is roughly same
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+ when tokenized
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  with our Indic tokenizer we created which can be found in our model repository [Pragna-1b](https://huggingface.co/soketlabs/pragna-1b).
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  Here are token counts for each language:
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  - English: 196.2 millions
 
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  Each description column in different languages is a list of sentences/multiple sentences and can be concatenated to get cleaned article decription.
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  Each row is of the format:
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+ ```yaml
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  {'id': '1',
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  'url': 'https://simple.wikipedia.org/sample_article',
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  'title': 'Sample article',