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The dataset generation failed
Error code: DatasetGenerationError Exception: ArrowNotImplementedError Message: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field. Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 583, in write_table self._build_writer(inferred_schema=pa_table.schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer self.pa_writer = self._WRITER_CLASS(self.stream, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__ self.writer = _parquet.ParquetWriter( File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__ 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.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2027, in _prepare_split_single num_examples, num_bytes = writer.finalize() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 602, in finalize self._build_writer(self.schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer self.pa_writer = self._WRITER_CLASS(self.stream, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__ self.writer = _parquet.ParquetWriter( File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__ 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.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1529, in compute_config_parquet_and_info_response parquet_operations = convert_to_parquet(builder) File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1154, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
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_data_files
list | _fingerprint
string | _format_columns
sequence | _format_kwargs
dict | _format_type
null | _output_all_columns
bool | _split
null |
---|---|---|---|---|---|---|
[
{
"filename": "data-00000-of-00001.arrow"
}
] | 9e2a184c98898aa7 | [
"feat_example_id",
"target",
"text"
] | {} | null | false | null |
AutoTrain Dataset for project: tessst2
Dataset Description
This dataset has been automatically processed by AutoTrain for project tessst2.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"feat_example_id": 0,
"text": "\u0648\u062a\u062d\u062a \u0639\u0646\u0648\u0627\u0646 \u0645\u0646 \u0627\u0644\u0643\u0627\u0631\u062b\u0629 \u0625\u0644\u0649 \u0627\u0644\u062a\u062d\u062f\u0649 \u064a\u0628\u062f\u0623 \u0627\u0644\u0643\u0627\u062a\u0628 \u0639\u0631\u0636 \u0627\u0644\u0643\u062a\u0627\u0628 \u0627\u0644\u0631\u0627\u0628\u0639 \u060c \u062d\u064a\u062b \u064a\u0648\u0636\u062d \u0643\u064a\u0641 \u0643\u0627\u0646\u062a \u0625\u0633\u0631\u0627\u0626\u064a\u0644 \u0641\u0631\u062d\u0629 \u0628\u0646\u0635\u0631\u0647\u0627 \u0639\u0627\u0645 67 \u0648\u0623\u0646\u0647\u0627 \u0627\u0631\u062a\u0627\u062d\u062a \u0644\u0627\u0639\u062a\u0642\u0627\u062f\u0647\u0627 \u0628\u0623\u0646 \u0647\u0646\u0627\u0643 \u0648\u0642\u062a\u0627 \u0637\u0648\u064a\u0644\u0627 \u0648\u0637\u0648\u064a\u0644\u0627 \u062c\u062f\u0627 \u0642\u0628\u0644 \u0623\u0646 \u064a\u0641\u064a\u0642 \u0627\u0644\u0639\u0631\u0628 \u0645\u0646 \u0635\u062f\u0645\u0629 67\u060c \u0648\u0643\u064a\u0641 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},
{
"feat_example_id": 1,
"text": "\u0648\u0644\u0645 \u064a\u0639\u062a\u0631\u0641 \u062f\u0628\u0644\u0648\u0645\u0627\u0633\u064a\u0648 \u0647\u0627\u062a\u064a\u0646 \u0627\u0644\u062f\u0648\u0644\u062a\u064a\u0646 \u0628\u0627\u0644\u0639\u0631\u064a\u0636\u0629 \u0627\u0644\u062a\u064a \u0648\u0642\u0639\u0647\u0627 \u0627\u0644\u0623\u0639\u064a\u0627\u0646 \u060c \u0625\u0630 \u0627\u0639\u062a\u0628\u0631\u0648\u0647\u0627 \u0645\u062d\u0627\u0648\u0644\u0629 \u0641\u0642\u0637 \u0645\u0646 \u0633\u0644\u0637\u0627\u062a \u0627\u0644\u062d\u0645\u0627\u064a\u0629 \u0644\u0625\u062c\u0628\u0627\u0631 \u0627\u0644\u0633\u0644\u0637\u0627\u0646 \u0639\u0644\u0649 \u0642\u0628\u0648\u0644 \u0645\u062e\u0637\u0637\u0627\u062a\u0647\u0627 \u0648\u0630\u0644\u0643 \u0628\u0627\u0644\u062a\u0648\u0642\u064a\u0639 \u0639\u0644\u0649 \u0627\u0644\u0638\u0647\u0627\u0626\u0631 . \u0623\u0645\u0627 \u0645\u0639\u0627\u0631\u0636\u0629 \u0627\u0644\u062f\u0648\u0644 \u0627\u0644\u0639\u0631\u0628\u064a\u0629 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"target": "\u062f\u0628\u0644\u0648\u0645\u0627\u0633\u064a\u0648 \u0627\u0644\u062f\u0648\u0644\u062a\u064a\u0646 \u0644\u0645 \u064a\u0639\u062a\u0631\u0641\u0648\u0627 \u0628\u0627\u0644\u0639\u0631\u064a\u0636\u0629 \u0627\u0644\u062a\u064a \u0642\u0627\u0645 \u0627\u0644\u0623\u0639\u064a\u0627\u0646 \u0628\u062a\u0648\u0642\u064a\u0639\u0647\u0627, \u0648\u0645\u0639\u0627\u0631\u0636\u0629 \u0627\u0644\u062f\u0648\u0644 \u0627\u0644\u0639\u0631\u0628\u064a\u0629 \u0648\u0627\u0644\u0622\u0633\u064a\u0648\u064a\u0629 \u0643\u0627\u0646\u062a \u062a\u0639\u062a\u0628\u0631 \u062d\u0645\u0644\u0629 \u0634\u0631\u0633\u0629 \u0636\u062f \u0627\u0644\u0625\u062c\u0631\u0627\u0621 \u0627\u0644\u0641\u0631\u0646\u0633\u064a \u0639\u0646 \u0637\u0631\u064a\u0642 \u0627\u0644\u0635\u062d\u0627\u0641\u0629, \u0648\u0642\u0627\u0645 \u0639\u0644\u0627\u0644 \u0627\u0644\u0641\u0627\u0633\u064a \u0642\u0627\u0644 \u0641\u064a \u0625\u0630\u0627\u0639\u0629 \u0627\u0644\u0642\u0627\u0647\u0631\u0629 \u0639\u0646 \u062a\u0646\u062d\u064a\u0629 \u0627\u0644\u0633\u0644\u0637\u0627\u0646 \u0648\u0639\u0627\u0626\u0644\u062a\u0647 \u0639\u0646 \u0627\u0644\u0648\u0637\u0646, \u0648\u0627\u0644\u0645\u0639\u0627\u0647\u062f\u0629 \u0627\u0644\u0630\u064a \u062d\u062f\u062b\u062a \u0628\u064a\u0646 \u0627\u0644\u0628\u0644\u062f\u064a\u0646 \u0643\u0627\u0646\u062a \u062a\u0646\u0635 \u0628\u0627\u0644\u062a\u0632\u0627\u0645 \u0627\u0644\u0625\u062d\u062a\u0631\u0627\u0645 \u0644\u0644\u0625\u0645\u0628\u0631\u0627\u0637\u0648\u0631\u064a\u0629 \u0627\u0644\u0634\u0631\u064a\u0641\u0629, \u0648\u0639\u0645\u0644\u064a\u0629 \u062a\u0646\u0635\u064a\u0628 \u0633\u0644\u0637\u0627\u0646 \u062c\u062f\u064a\u062f \u0639\u0644\u0649 \u0627\u0644\u0645\u063a\u0631\u0628 \u0641\u064a \u0623\u0633\u0628\u0627\u0646\u064a\u0627 \u0623\u062e\u0630\u062a \u0627\u0644\u0631\u0641\u0636."
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"feat_example_id": "Value(dtype='int64', id=None)",
"text": "Value(dtype='string', id=None)",
"target": "Value(dtype='string', id=None)"
}
Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
Split name | Num samples |
---|---|
train | 154 |
valid | 154 |
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