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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
bos_token: struct<content: string, lstrip: bool, normalized: bool, rstrip: bool, single_word: bool>
child 0, content: string
child 1, lstrip: bool
child 2, normalized: bool
child 3, rstrip: bool
child 4, single_word: bool
eos_token: struct<content: string, lstrip: bool, normalized: bool, rstrip: bool, single_word: bool>
child 0, content: string
child 1, lstrip: bool
child 2, normalized: bool
child 3, rstrip: bool
child 4, single_word: bool
pad_token: struct<content: string, lstrip: bool, normalized: bool, rstrip: bool, single_word: bool>
child 0, content: string
child 1, lstrip: bool
child 2, normalized: bool
child 3, rstrip: bool
child 4, single_word: bool
unk_token: struct<content: string, lstrip: bool, normalized: bool, rstrip: bool, single_word: bool>
child 0, content: string
child 1, lstrip: bool
child 2, normalized: bool
child 3, rstrip: bool
child 4, single_word: bool
timestamp: timestamp[s]
configuration: struct<tokenizer: string, max_sequence_length: int64, chat_template: string>
child 0, tokenizer: string
child 1, max_sequence_length: int64
child 2, chat_template: string
per_dataset_statistics: list<item: struct<dataset_name: string, dataset_split: string, initial_instances: int64, instances_a (... 443 chars omitted)
child 0, item: struct<dataset_name: string, dataset_split: string, initial_instances: int64, instances_after_transf (... 431 chars omitted)
child 0, dataset_name: string
child 1, dataset_split: string
child 2, initial_instances: int64
child 3, instances_after_transformation: int64
child 4, instances_filtered_during_transformation: int64
child 5, frac_or_num_samples: double
child 6, original_dataset_size: int64
child 7, is_upsampled: bool
child 8, upsampling_factor: double
child 9, final_instances_in_output: int64
child 10, final_tokens_in_output: int64
child 11, final_trainable_tokens_in_output: int64
child 12, instances_filtered_after_tokenization: int64
child 13, avg_tokens_per_instance: double
child 14, percentage_of_total_tokens: double
child 15, percentage_of_total_instances: double
output_directory: string
overall_statistics: struct<total_datasets: int64, total_instances: int64, total_tokens: int64, trainable_tokens: int64, (... 89 chars omitted)
child 0, total_datasets: int64
child 1, total_instances: int64
child 2, total_tokens: int64
child 3, trainable_tokens: int64
child 4, trainable_percentage: double
child 5, instances_filtered: int64
child 6, average_sequence_length: double
to
{'timestamp': Value('timestamp[s]'), 'output_directory': Value('string'), 'configuration': {'tokenizer': Value('string'), 'max_sequence_length': Value('int64'), 'chat_template': Value('string')}, 'per_dataset_statistics': List({'dataset_name': Value('string'), 'dataset_split': Value('string'), 'initial_instances': Value('int64'), 'instances_after_transformation': Value('int64'), 'instances_filtered_during_transformation': Value('int64'), 'frac_or_num_samples': Value('float64'), 'original_dataset_size': Value('int64'), 'is_upsampled': Value('bool'), 'upsampling_factor': Value('float64'), 'final_instances_in_output': Value('int64'), 'final_tokens_in_output': Value('int64'), 'final_trainable_tokens_in_output': Value('int64'), 'instances_filtered_after_tokenization': Value('int64'), 'avg_tokens_per_instance': Value('float64'), 'percentage_of_total_tokens': Value('float64'), 'percentage_of_total_instances': Value('float64')}), 'overall_statistics': {'total_datasets': Value('int64'), 'total_instances': Value('int64'), 'total_tokens': Value('int64'), 'trainable_tokens': Value('int64'), 'trainable_percentage': Value('float64'), 'instances_filtered': Value('int64'), 'average_sequence_length': Value('float64')}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 295, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
bos_token: struct<content: string, lstrip: bool, normalized: bool, rstrip: bool, single_word: bool>
child 0, content: string
child 1, lstrip: bool
child 2, normalized: bool
child 3, rstrip: bool
child 4, single_word: bool
eos_token: struct<content: string, lstrip: bool, normalized: bool, rstrip: bool, single_word: bool>
child 0, content: string
child 1, lstrip: bool
child 2, normalized: bool
child 3, rstrip: bool
child 4, single_word: bool
pad_token: struct<content: string, lstrip: bool, normalized: bool, rstrip: bool, single_word: bool>
child 0, content: string
child 1, lstrip: bool
child 2, normalized: bool
child 3, rstrip: bool
child 4, single_word: bool
unk_token: struct<content: string, lstrip: bool, normalized: bool, rstrip: bool, single_word: bool>
child 0, content: string
child 1, lstrip: bool
child 2, normalized: bool
child 3, rstrip: bool
child 4, single_word: bool
timestamp: timestamp[s]
configuration: struct<tokenizer: string, max_sequence_length: int64, chat_template: string>
child 0, tokenizer: string
child 1, max_sequence_length: int64
child 2, chat_template: string
per_dataset_statistics: list<item: struct<dataset_name: string, dataset_split: string, initial_instances: int64, instances_a (... 443 chars omitted)
child 0, item: struct<dataset_name: string, dataset_split: string, initial_instances: int64, instances_after_transf (... 431 chars omitted)
child 0, dataset_name: string
child 1, dataset_split: string
child 2, initial_instances: int64
child 3, instances_after_transformation: int64
child 4, instances_filtered_during_transformation: int64
child 5, frac_or_num_samples: double
child 6, original_dataset_size: int64
child 7, is_upsampled: bool
child 8, upsampling_factor: double
child 9, final_instances_in_output: int64
child 10, final_tokens_in_output: int64
child 11, final_trainable_tokens_in_output: int64
child 12, instances_filtered_after_tokenization: int64
child 13, avg_tokens_per_instance: double
child 14, percentage_of_total_tokens: double
child 15, percentage_of_total_instances: double
output_directory: string
overall_statistics: struct<total_datasets: int64, total_instances: int64, total_tokens: int64, trainable_tokens: int64, (... 89 chars omitted)
child 0, total_datasets: int64
child 1, total_instances: int64
child 2, total_tokens: int64
child 3, trainable_tokens: int64
child 4, trainable_percentage: double
child 5, instances_filtered: int64
child 6, average_sequence_length: double
to
{'timestamp': Value('timestamp[s]'), 'output_directory': Value('string'), 'configuration': {'tokenizer': Value('string'), 'max_sequence_length': Value('int64'), 'chat_template': Value('string')}, 'per_dataset_statistics': List({'dataset_name': Value('string'), 'dataset_split': Value('string'), 'initial_instances': Value('int64'), 'instances_after_transformation': Value('int64'), 'instances_filtered_during_transformation': Value('int64'), 'frac_or_num_samples': Value('float64'), 'original_dataset_size': Value('int64'), 'is_upsampled': Value('bool'), 'upsampling_factor': Value('float64'), 'final_instances_in_output': Value('int64'), 'final_tokens_in_output': Value('int64'), 'final_trainable_tokens_in_output': Value('int64'), 'instances_filtered_after_tokenization': Value('int64'), 'avg_tokens_per_instance': Value('float64'), 'percentage_of_total_tokens': Value('float64'), 'percentage_of_total_instances': Value('float64')}), 'overall_statistics': {'total_datasets': Value('int64'), 'total_instances': Value('int64'), 'total_tokens': Value('int64'), 'trainable_tokens': Value('int64'), 'trainable_percentage': Value('float64'), 'instances_filtered': Value('int64'), 'average_sequence_length': Value('float64')}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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