crux82/squad_it
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How to use luigisaetta/squad_it_xxl_cased_hub1 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="luigisaetta/squad_it_xxl_cased_hub1") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("luigisaetta/squad_it_xxl_cased_hub1")
model = AutoModelForQuestionAnswering.from_pretrained("luigisaetta/squad_it_xxl_cased_hub1", device_map="auto")This is a model, based on BERT trained on cased Italian, that can be used for Extractive Q&A on Italian texts.
This model has been trained on squad_it dataset starting from the pre-trained model dbmdz/bert-base-italian-xxl-cased.
These are the metrics computed on evaluation set:
from transformers import pipeline
pipe_qa = pipeline('question-answering', model='luigisaetta/squad_it_xxl_cased_hub1')
pipe_qa(context="Io sono nato a Napoli. Il mare bagna Napoli. Napoli è la più bella città del mondo",
question="Qual è la più bella città del mondo?")
This model can be used for Extractive Q&A on Italian Text
see code in this NoteBook
The following hyperparameters were used during training: