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  This is an uncased <b>BERT</b> <b>[1]</b> model for the <b>Italian</b> language, obtained using the uncased <b>mBERT</b> ([bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased)) as a starting point and focusing it on the Italian language by modifying the embedding layer
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  (as in <b>[2]</b>, computing document-level frequencies over the <b>Wikipedia</b> dataset)
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- The resulting model has 110M parameters, a vocabulary of 30.785 tokens, and a size of ~430 MB.
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  <h3>Quick usage</h3>
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  This is an uncased <b>BERT</b> <b>[1]</b> model for the <b>Italian</b> language, obtained using the uncased <b>mBERT</b> ([bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased)) as a starting point and focusing it on the Italian language by modifying the embedding layer
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  (as in <b>[2]</b>, computing document-level frequencies over the <b>Wikipedia</b> dataset)
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+ The resulting model has 110M parameters, a vocabulary of 30.154 tokens, and a size of ~430 MB.
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  <h3>Quick usage</h3>
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