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<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: DistilBERT</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>

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<h3>Model description</h3>

This is a <b>DistilBERT</b> <b>[1]</b> model for the <b>Italian</b> language, obtained using the multilingual <b>DistilBERT</b> ([distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased)) as a starting point and focusing it on the Italian language by modifying the embedding layer 
(as in <b>[2]</b>, computing document-level frequencies over the <b>Wikipedia</b> dataset)

The resulting model has 67M parameters, a vocabulary of 30.785 tokens, and a size of ~270 MB.

<h3>Quick usage</h3>

```python
from transformers import BertTokenizerFast, DistilBertModel

tokenizer = DistilBertTokenizerFast.from_pretrained("osiria/distilbert-base-italian-cased")
model = DistilBertModel.from_pretrained("osiria/distilbert-base-italian-cased")
```

<h3>References</h3>

[1] https://arxiv.org/abs/1910.01108

[2] https://arxiv.org/abs/2010.05609

<h3>License</h3>

The model is released under <b>Apache-2.0</b> license

{"language": ["it"], "license": "apache-2.0"}
transformers pytorch safetensors distilbert fill-mask it arxiv:1910.01108 arxiv:2010.05609 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #distilbert #fill-mask #it #arxiv-1910.01108 #arxiv-2010.05609 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

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<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: DistilBERT</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>DistilBERT</b> <b>[1]</b> model for the <b>Italian</b> language, obtained using the multilingual <b>DistilBERT</b> (distilbert-base-multilingual-cased) as a starting point and focusing it on the Italian language by modifying the embedding layer 
(as in <b>[2]</b>, computing document-level frequencies over the <b>Wikipedia</b> dataset)

The resulting model has 67M parameters, a vocabulary of 30.785 tokens, and a size of ~270 MB.

<h3>Quick usage</h3>



<h3>References</h3>

[1] URL

[2] URL

<h3>License</h3>

The model is released under <b>Apache-2.0</b> license

TAGS
#transformers #pytorch #safetensors #distilbert #fill-mask #it #arxiv-1910.01108 #arxiv-2010.05609 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
