Osiria
Rank:Average Model Cost: $0.0000
Number of Runs: 16,392
Models by this creator
bert-italian-cased-ner
$-/run
3.8K
Huggingface
deberta-italian-question-answering
deberta-italian-question-answering
Platform did not provide a description for this model.
$-/run
2.0K
Huggingface
bert-tweet-italian-uncased-sentiment
$-/run
1.8K
Huggingface
bert-italian-uncased-ner
$-/run
1.7K
Huggingface
distilbert-italian-cased-ner
$-/run
1.7K
Huggingface
distilbert-base-italian-cased
$-/run
1.1K
Huggingface
deberta-base-italian
deberta-base-italian
Model description This is a DeBERTa [1] model for the Italian language, obtained using mDeBERTa (mdeberta-v3-base) as a starting point and focusing it on the Italian language by modifying the embedding layer (as in [2], computing document-level frequencies over the Wikipedia dataset) The resulting model has 124M parameters, a vocabulary of 50.256 tokens, and a size of ~500 MB. Quick usage References [1] https://arxiv.org/abs/2111.09543 [2] https://arxiv.org/abs/2010.05609 License The model is released under MIT license
$-/run
1.1K
Huggingface
bert-base-italian-uncased
$-/run
1.0K
Huggingface
bert-base-italian-cased
$-/run
1.0K
Huggingface
bert-tweet-base-italian-uncased
bert-tweet-base-italian-uncased
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 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
$-/run
1.0K
Huggingface