Question Answering Datasets
Explore a wide range of question answering datasets for pre-trained models, including SQuAD, TriviaQA, and Natural Questions.
Explore a wide range of question answering datasets for pre-trained models, including SQuAD, TriviaQA, and Natural Questions.
Stanford Natural Language Processing Group provides various question answering datasets, such as Stanford Question Answering Dataset (SQuAD) and WikiQA.
Discover pre-trained models for question answering tasks, including BERT, RoBERTa, and XLNet, and learn how to fine-tune them on your dataset.
Access a repository of question answering datasets from government sources, including datasets on healthcare, education, and finance.
Evaluate the performance of your question answering model on the NLP Question Answering Benchmark, featuring a range of datasets and evaluation metrics.
Learn how to use transformer-based pre-trained models for question answering tasks, including code examples and tutorials.
Explore a dataset for question answering in low-resource languages, developed by the United Nations, to improve language understanding and accessibility.
Watch a tutorial on building a question answering system using pre-trained models, covering dataset preparation, model fine-tuning, and evaluation.