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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"
}
] | 55e49768f323208c | [
"feat_id",
"target",
"text"
] | {} | null | false | null |
AutoTrain Dataset for project: lwf-summarization
Dataset Description
This dataset has been automatically processed by AutoTrain for project lwf-summarization.
Languages
The BCP-47 code for the dataset's language is zh.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"feat_id": "13716782",
"target": "The scariest place for Jessica was the Capuchin Catacombs in Palermo.",
"text": "Kelly: Oh! Oh! Can I pick the first question?\r\nJessica: Sure. Go for it!\r\nKelly: What's the scariest place you've been to!\r\nJessica: I'll start: Palermo in Italy.\r\nMickey: And what's so scary about that? Did you break your nail? :P\r\nJessica: Shut it, Mickey! No, there are the Capuchin Catacombs with 8000 corpses! \r\nKelly: Ewwww! Corpses? Rly?\r\nJessica: Yeah! And you can look at them like museum exhibits. I think they're divided somehow, but have no clue how!\r\nOllie: That's so cool! Do you get to see the bones or are they covered up?\r\nJessica: Well, partly. Most of them were exhibited in their clothes. Basically only skulls and hands. \r\nMickey: I'm writing this one down! That's so precious!\r\nOllie: Me too!"
},
{
"feat_id": "13716592",
"target": "Carrie and Gina saw \"Fantastic Beast\" and liked it. Ginna loved Eddie Redmayne as Newt. ",
"text": "Carrie: Just back from Fantastic Beast :)\r\nGina: and what do you think?\r\nCarrie: generally good - as usual nice special effect and visuals, an ok plot, a glimpse of the wizarding community in the US.\r\nAlex: Sounds cool. I was thinking of going this weekend with Lane, but I've seen some bad reviews.\r\nCarrie: Depends on what you expect really - I have a lot of sentiment towards Harry Potter so, I'm gonna like everything the do. But seriously the movie was decent. However, if you're expecting to have your mind blown, then no, it's not THAT good.\r\nGina: I agree. I saw it last week and basically I'm satisfied.\r\nAlex: No spoilers, girls.\r\nCarrie: no worries ;)\r\nCarrie: And Gina, what do you think about Eddie Redmayne as Newt?\r\nGina: I loved him <3 I loved how introverted and awkward he was and how caring he was towards the animals. And with all that he showed a lot of confidence in his beliefs and was a genuinely compassionate character\r\nCarrie: not your standard protagonist, that's for sure\r\nGina: and that's what I liked about him\r\nAlex: Maybe I'll go and see it sooner so we can all talk about it.\r\nCarrie: go see it. If' you're not expecting god-knows-what you're going to enjoy it ;)"
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"feat_id": "Value(dtype='string', id=None)",
"target": "Value(dtype='string', id=None)",
"text": "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 | 655 |
valid | 164 |
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