Model: BERT-TWEET
Lang: IT
Model description
This is a BERT [1] uncased model for the Italian language, obtained using TwHIN-BERT [2] (twhin-bert-base) as a starting point and focusing it on the Italian language by modifying the embedding layer (as in [3], computing document-level frequencies over the Wikipedia dataset)
The resulting model has 110M parameters, a vocabulary of 30.520 tokens, and a size of ~440 MB.
Quick usage
from transformers import BertTokenizerFast, BertModel
tokenizer = BertTokenizerFast.from_pretrained("osiria/bert-tweet-base-italian-uncased")
model = BertModel.from_pretrained("osiria/bert-tweet-base-italian-uncased")
Here you can find the find the model already fine-tuned on Sentiment Analysis: https://huggingface.co/osiria/bert-tweet-italian-uncased-sentiment
References
[1] https://arxiv.org/abs/1810.04805
[2] https://arxiv.org/abs/2209.07562
[3] https://arxiv.org/abs/2010.05609
Limitations
This model was trained on tweets, so it's mainly suitable for general-purpose social media text processing, involving short texts written in a social network style. It might show limitations when it comes to longer and more structured text, or domain-specific text.
License
The model is released under Apache-2.0 license
- Downloads last month
- 29