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Error code: FeaturesError Exception: ArrowInvalid Message: JSON parse error: Column(/metadata/toxicity/[]/[]) changed from string to number in row 0 Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 160, in _generate_tables df = pandas_read_json(f) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json return pd.read_json(path_or_buf, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 815, in read_json return json_reader.read() File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1025, in read obj = self._get_object_parser(self.data) File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1051, in _get_object_parser obj = FrameParser(json, **kwargs).parse() File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1187, in parse self._parse() File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1403, in _parse ujson_loads(json, precise_float=self.precise_float), dtype=None ValueError: Trailing data 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 231, 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 163, in _generate_tables raise e 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(/metadata/toxicity/[]/[]) changed from string to number in row 0
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This is a copy of a subset of the youtube_commons dataset which includes transcripts from CC-BY-* youtube videos. We have run the trancript through a cleanup model to cleanup the text and add punctuations. This is by no means perfect, and there are still lots of grammatical issues. We then combined all transcripts from the same video into one data time, separated by <|endoftext|>. When possible, we included English text first.
Where there was no English text, we machine translated the first few words of the text into English and prepended the English text.
We added some basic formatting such as "Title:", and "Transcript:".
Also we ran the English text through a toxicity model and recorded the results.
Lastly we used an edu scorer to score the text for educaitonal value.
The intended use of this dataset is to create augmented multilingual data for training a model. We recommend you run this data through for example, an LLM to extract useful information or reformat to stories, textbooks, etc.
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