# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("crodri/roberta-base-ca-v2-qa-catalanqa")
model = AutoModelForQuestionAnswering.from_pretrained("crodri/roberta-base-ca-v2-qa-catalanqa")Quick Links
The roberta-base-ca-cased-qa is a Question Answering (QA) model for the Catalan language fine-tuned from the BERTa model, a RoBERTa base model pre-trained on a medium-size corpus collected from publicly available corpora and crawlers (check the BERTa model card for more details).
Datasets
We used the Catalan QA datasets called ViquiQuAD, VilaQuad and XQuad_ca with test, training and evaluation (90-10-10) splits, balanced by type of questions.
Test: 2255 Evaluation: 2276 Train: 18082
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="crodri/roberta-base-ca-v2-qa-catalanqa")