Osiria "Earth" Series 🌱
Collection
This collection is composed of robust and reliable models for common NLP tasks • 10 items • Updated • 1
How to use osiria/bert-base-italian-uncased with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("fill-mask", model="osiria/bert-base-italian-uncased") # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("osiria/bert-base-italian-uncased")
model = AutoModelForMaskedLM.from_pretrained("osiria/bert-base-italian-uncased")This is an uncased BERT [1] model for the Italian language, obtained using the uncased mBERT (bert-base-multilingual-uncased) 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 110M parameters, a vocabulary of 30.154 tokens, and a size of ~430 MB.
from transformers import BertTokenizerFast, BertModel
tokenizer = BertTokenizerFast.from_pretrained("osiria/bert-base-italian-uncased")
model = BertModel.from_pretrained("osiria/bert-base-italian-uncased")
[1] https://arxiv.org/abs/1810.04805
[2] https://arxiv.org/abs/2010.05609
The model is released under Apache-2.0 license