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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError Exception: ValueError Message: Not able to read records in the JSON file at zip://1.json::hf://datasets/Cheliosoops/Open-Sora-Plan@3b9da3650b226651e8dfc4b1455ef7c96b6e31b4/urls_multipro_1.zip. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['A', 'I']. Select the correct one and provide it as `field='XXX'` to the dataset loading method. Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 240, 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 2216, 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 1239, 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 1389, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, 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 170, in _generate_tables raise ValueError( ValueError: Not able to read records in the JSON file at zip://1.json::hf://datasets/Cheliosoops/Open-Sora-Plan@3b9da3650b226651e8dfc4b1455ef7c96b6e31b4/urls_multipro_1.zip. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['A', 'I']. Select the correct one and provide it as `field='XXX'` to the dataset loading method.
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