<body> <span class="vertical-text" style="background-color:lightgreen;border-radius: 3px;padding: 3px;"> </span> <br> <span class="vertical-text" style="background-color:orange;border-radius: 3px;padding: 3px;"> </span> <br> <span class="vertical-text" style="background-color:lightblue;border-radius: 3px;padding: 3px;"> Model: RoBERTa</span> <br> <span class="vertical-text" style="background-color:tomato;border-radius: 3px;padding: 3px;"> Lang: IT</span> <br> <span class="vertical-text" style="background-color:lightgrey;border-radius: 3px;padding: 3px;"> </span> <br> <span class="vertical-text" style="background-color:#CF9FFF;border-radius: 3px;padding: 3px;"> </span> </body>
<h3>Model description</h3>
This is a <b>RoBERTa</b> <b>[1]</b> model for the <b>Italian</b> language, obtained using <b>XLM-RoBERTa</b> <b>[2]</b> (xlm-roberta-base) as a starting point and focusing it on the italian language by modifying the embedding layer (as in <b>[3]</b>, computing document-level frequencies over the <b>Wikipedia</b> dataset)
The resulting model has 125M parameters, a vocabulary of 50.670 tokens, and a size of ~500 MB.
<h3>Quick usage</h3>
from transformers import RobertaTokenizerFast, RobertaModel
tokenizer = RobertaTokenizerFast.from_pretrained("osiria/roberta-base-italian")
model = RobertaModel.from_pretrained("osiria/roberta-base-italian")
<h3>References</h3>
[1] https://arxiv.org/abs/1907.11692
[2] https://arxiv.org/abs/1911.02116
[3] https://arxiv.org/abs/2010.05609
<h3>License</h3>
The model is released under <b>MIT</b> license
