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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    LibsndfileError
Message:      Error opening <_io.BytesIO object at 0x7f1eb4870680>: Format not recognised.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute
                  compute_first_rows_from_parquet_response(
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response
                  rows_index = indexer.get_rows_index(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 640, in get_rows_index
                  return RowsIndex(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 521, in __init__
                  self.parquet_index = self._init_parquet_index(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 538, in _init_parquet_index
                  response = get_previous_step_or_raise(
                File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise
                  raise CachedArtifactError(
              libcommon.simple_cache.CachedArtifactError: The previous step failed.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 96, in get_rows_or_raise
                  return get_rows(
                File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 73, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1393, in __iter__
                  example = _apply_feature_types_on_example(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1082, in _apply_feature_types_on_example
                  decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1983, in decode_example
                  return {
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1984, in <dictcomp>
                  column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1349, in decode_nested_example
                  return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/audio.py", line 187, in decode_example
                  array, sampling_rate = sf.read(file)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/soundfile.py", line 285, in read
                  with SoundFile(file, 'r', samplerate, channels,
                File "/src/services/worker/.venv/lib/python3.9/site-packages/soundfile.py", line 658, in __init__
                  self._file = self._open(file, mode_int, closefd)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/soundfile.py", line 1216, in _open
                  raise LibsndfileError(err, prefix="Error opening {0!r}: ".format(self.name))
              soundfile.LibsndfileError: Error opening <_io.BytesIO object at 0x7f1eb4870680>: Format not recognised.

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LAION-Debate's audio files worth 110GB is available on this dataset repo. Please download them using git and a script will be made available to preprocess the dataset.

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