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/roberta-base-italian with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("fill-mask", model="osiria/roberta-base-italian") # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("osiria/roberta-base-italian")
model = AutoModelForMaskedLM.from_pretrained("osiria/roberta-base-italian")This is a RoBERTa [1] model for the Italian language, obtained using XLM-RoBERTa [2] (xlm-roberta-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 125M parameters, a vocabulary of 50.670 tokens, and a size of ~500 MB.
from transformers import RobertaTokenizerFast, RobertaModel
tokenizer = RobertaTokenizerFast.from_pretrained("osiria/roberta-base-italian")
model = RobertaModel.from_pretrained("osiria/roberta-base-italian")
[1] https://arxiv.org/abs/1907.11692
[2] https://arxiv.org/abs/1911.02116
[3] https://arxiv.org/abs/2010.05609
The model is released under MIT license