Error code:   ConfigNamesError
Exception:    RuntimeError
Message:      Dataset scripts are no longer supported, but found faquad.py
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1029, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 989, in dataset_module_factory
                  raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
              RuntimeError: Dataset scripts are no longer supported, but found faquad.py

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Dataset Card for FaQuAD

Dataset Summary

Academic secretaries and faculty members of higher education institutions face a common problem: the abundance of questions sent by academics whose answers are found in available institutional documents. The official documents produced by Brazilian public universities are vast and disperse, which discourage students to further search for answers in such sources. In order to lessen this problem, we present FaQuAD: a novel machine reading comprehension dataset in the domain of Brazilian higher education institutions. FaQuAD follows the format of SQuAD (Stanford Question Answering Dataset) [Rajpurkar et al. 2016]. It comprises 900 questions about 249 reading passages (paragraphs), which were taken from 18 official documents of a computer science college from a Brazilian federal university and 21 Wikipedia articles related to Brazilian higher education system. As far as we know, this is the first Portuguese reading comprehension dataset in this format.