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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowTypeError
Message: ("Expected bytes, got a 'list' object", 'Conversion failed for column 262146001 with type object')
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 137, in _generate_tables
pa_table = paj.read_json(
File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 233, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, 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 1918, 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 2093, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__
for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 167, in _generate_tables
pa_table = pa.Table.from_pandas(df, preserve_index=False)
File "pyarrow/table.pxi", line 3874, in pyarrow.lib.Table.from_pandas
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 611, in dataframe_to_arrays
arrays = [convert_column(c, f)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 611, in <listcomp>
arrays = [convert_column(c, f)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 598, in convert_column
raise e
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 592, in convert_column
result = pa.array(col, type=type_, from_pandas=True, safe=safe)
File "pyarrow/array.pxi", line 339, in pyarrow.lib.array
File "pyarrow/array.pxi", line 85, in pyarrow.lib._ndarray_to_array
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowTypeError: ("Expected bytes, got a 'list' object", 'Conversion failed for column 262146001 with type object')Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for ViVQA-X
Dataset Description
ViVQA-X is the Vietnamese version of the Visual Question Answering Explanation (VQA-X) dataset, designed for tasks in VQA-NLE in the Vietnamese language. This dataset was created to support research in Vietnamese VQA, offering translated examples with explanations, in alignment with the original English dataset. The ViVQA-X dataset is generated using a multi-stage pipeline for translation and evaluation, including both automated translation and post-processing, with quality evaluations involving multiple large language models (LLMs).
Dataset statistics
- QA Pairs: 32,886 pairs of questions and answers across Train, Validation, and Test splits.
- Explanations: 41,817 high-quality explanations.
- Average Words: Explanations average 10 words per explanation.
- Vocabulary Size: 4,232 unique words in explanations.
If you mention or use any information from our dataset, please cite our paper:
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