The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'test' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ValueError
Message: Not able to read records in the JSON file at hf://datasets/deepset/stackoverflow-survey-2023-text-sql@ab41077da0236718911d79698f279c0221281704/eval_set_multi_answers_res.json.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows_from_streaming.py", line 132, in compute_first_rows_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2211, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1235, in _head
return _examples_to_batch(list(self.take(n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1384, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1040, in __iter__
yield from islice(self.ex_iterable, self.n)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__
for key, pa_table in self.generate_tables_fn(**self.kwargs):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 156, in _generate_tables
raise ValueError(f"Not able to read records in the JSON file at {file}.") from None
ValueError: Not able to read records in the JSON file at hf://datasets/deepset/stackoverflow-survey-2023-text-sql@ab41077da0236718911d79698f279c0221281704/eval_set_multi_answers_res.json.Need help to make the dataset viewer work? Open a discussion for direct support.
BIQA Text-to-SQL Dataset
The data is from the Stack Overflow Developer Survey 2023.
Created with this Notebook; uses this spreadsheet defining manual adjustments.
data/eval_set_multi_answers_res.json: Question and query pairs as list ofSQLSamples with possibly more than one valid SQL for a question. Also results included.data/survey_results_normalized_v2.db: The main sqlite db file.
The json file contains a list of SQLSample objects as defined:
@dataclass
class SQLQuery:
query: str
results: Optional[list[tuple]] = None
@dataclass
class SQLSample:
question: str
labels: list[SQLQuery]
prediction: Optional[SQLQuery] = None
pred_eval: str = ""
comment: str = ""
Can be read in through the code from the related repository.
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