Dataset Viewer
Duplicate
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:    CastError
Message:      Couldn't cast
source: string
generated_at: timestamp[s]
record_count: int64
records: list<item: struct<feedback_id: string, customer_id: string, channel: string, product_name: string, c (... 96 chars omitted)
  child 0, item: struct<feedback_id: string, customer_id: string, channel: string, product_name: string, category: st (... 84 chars omitted)
      child 0, feedback_id: string
      child 1, customer_id: string
      child 2, channel: string
      child 3, product_name: string
      child 4, category: string
      child 5, rating: int64
      child 6, review_text: string
      child 7, review_date: timestamp[s]
      child 8, status: string
report: struct<report_id: string, generated_at: timestamp[s], source_repo: string, record_count: int64, cate (... 447 chars omitted)
  child 0, report_id: string
  child 1, generated_at: timestamp[s]
  child 2, source_repo: string
  child 3, record_count: int64
  child 4, category_counts: struct<positive: int64, neutral: int64, negative: int64>
      child 0, positive: int64
      child 1, neutral: int64
      child 2, negative: int64
  child 5, action_counts: struct<routine: int64, review: int64, escalation: int64, high_escalation: int64>
      child 0, routine: int64
      child 1, review: int64
      child 2, escalation: int64
      child 3, high_escalation: int64
  child 6, summary_recommendation: string
  child 7, records: list<item: struct<feedback_id: string, customer_id: string, channel: string, product_name: string, c (... 137 chars omitted)
      child 0, item: struct<feedback_id: string, customer_id: string, channel: string, product_name: string, category: st (... 125 chars omitted)
          child 0, feedback_id: string
          child 1, customer_id: string
          child 2, channel: string
          child 3, product_name: string
          child 4, category: string
          child 5, rating: int64
          child 6, review_text: string
          child 7, review_date: timestamp[s]
          child 8, status: string
          child 9, triage_category: string
          child 10, action: string
to
{'report': {'report_id': Value('string'), 'generated_at': Value('timestamp[s]'), 'source_repo': Value('string'), 'record_count': Value('int64'), 'category_counts': {'positive': Value('int64'), 'neutral': Value('int64'), 'negative': Value('int64')}, 'action_counts': {'routine': Value('int64'), 'review': Value('int64'), 'escalation': Value('int64'), 'high_escalation': Value('int64')}, 'summary_recommendation': Value('string'), 'records': List({'feedback_id': Value('string'), 'customer_id': Value('string'), 'channel': Value('string'), 'product_name': Value('string'), 'category': Value('string'), 'rating': Value('int64'), 'review_text': Value('string'), 'review_date': Value('timestamp[s]'), 'status': Value('string'), 'triage_category': Value('string'), 'action': Value('string')})}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                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 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              source: string
              generated_at: timestamp[s]
              record_count: int64
              records: list<item: struct<feedback_id: string, customer_id: string, channel: string, product_name: string, c (... 96 chars omitted)
                child 0, item: struct<feedback_id: string, customer_id: string, channel: string, product_name: string, category: st (... 84 chars omitted)
                    child 0, feedback_id: string
                    child 1, customer_id: string
                    child 2, channel: string
                    child 3, product_name: string
                    child 4, category: string
                    child 5, rating: int64
                    child 6, review_text: string
                    child 7, review_date: timestamp[s]
                    child 8, status: string
              report: struct<report_id: string, generated_at: timestamp[s], source_repo: string, record_count: int64, cate (... 447 chars omitted)
                child 0, report_id: string
                child 1, generated_at: timestamp[s]
                child 2, source_repo: string
                child 3, record_count: int64
                child 4, category_counts: struct<positive: int64, neutral: int64, negative: int64>
                    child 0, positive: int64
                    child 1, neutral: int64
                    child 2, negative: int64
                child 5, action_counts: struct<routine: int64, review: int64, escalation: int64, high_escalation: int64>
                    child 0, routine: int64
                    child 1, review: int64
                    child 2, escalation: int64
                    child 3, high_escalation: int64
                child 6, summary_recommendation: string
                child 7, records: list<item: struct<feedback_id: string, customer_id: string, channel: string, product_name: string, c (... 137 chars omitted)
                    child 0, item: struct<feedback_id: string, customer_id: string, channel: string, product_name: string, category: st (... 125 chars omitted)
                        child 0, feedback_id: string
                        child 1, customer_id: string
                        child 2, channel: string
                        child 3, product_name: string
                        child 4, category: string
                        child 5, rating: int64
                        child 6, review_text: string
                        child 7, review_date: timestamp[s]
                        child 8, status: string
                        child 9, triage_category: string
                        child 10, action: string
              to
              {'report': {'report_id': Value('string'), 'generated_at': Value('timestamp[s]'), 'source_repo': Value('string'), 'record_count': Value('int64'), 'category_counts': {'positive': Value('int64'), 'neutral': Value('int64'), 'negative': Value('int64')}, 'action_counts': {'routine': Value('int64'), 'review': Value('int64'), 'escalation': Value('int64'), 'high_escalation': Value('int64')}, 'summary_recommendation': Value('string'), 'records': List({'feedback_id': Value('string'), 'customer_id': Value('string'), 'channel': Value('string'), 'product_name': Value('string'), 'category': Value('string'), 'rating': Value('int64'), 'review_text': Value('string'), 'review_date': Value('timestamp[s]'), 'status': Value('string'), 'triage_category': Value('string'), 'action': Value('string')})}}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Visual Question Answering Dataset

  • Samples: 18000
  • License: mit
  • Language: en

Description

Visual question answering dataset with images and answers.

Provenance

image-question pairs from a public visual QA benchmark

Usage

Intended for visual question answering research.

Downloads last month
104