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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
messages: list<item: struct<role: string, content: string>>
  child 0, item: struct<role: string, content: string>
      child 0, role: string
      child 1, content: string
quality: double
lang: string
source: string
pipeline: string
total_raw_entries: int64
timestamp: timestamp[s]
quality_threshold: double
total_gold_pairs: int64
to
{'total_raw_entries': Value('int64'), 'total_gold_pairs': Value('int64'), 'source': Value('string'), 'quality_threshold': Value('float64'), 'pipeline': Value('string'), 'timestamp': Value('timestamp[s]')}
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 299, 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
              messages: list<item: struct<role: string, content: string>>
                child 0, item: struct<role: string, content: string>
                    child 0, role: string
                    child 1, content: string
              quality: double
              lang: string
              source: string
              pipeline: string
              total_raw_entries: int64
              timestamp: timestamp[s]
              quality_threshold: double
              total_gold_pairs: int64
              to
              {'total_raw_entries': Value('int64'), 'total_gold_pairs': Value('int64'), 'source': Value('string'), 'quality_threshold': Value('float64'), 'pipeline': Value('string'), 'timestamp': Value('timestamp[s]')}
              because column names don't match

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Connor Gold v7

Certified 5.0/5.0 quality multilingual training pairs.
Only the top 0.5% of scored content passes the quality gate.

Dataset Summary

Gold v7 contains instruction-response pairs in 10 languages that have passed a strict quality certification (score ≥ 5.0/5.0). Each pair is formatted for direct use with chat-tuned language models using the ChatML format.

Languages

Language Code Coverage
English en Full
French fr Full
Spanish es Full
German de Full
Italian it Full
Portuguese pt Full
Russian ru Full
Arabic ar Full
Japanese ja Full
Korean ko Full

Data Format

Each entry is a JSON object with ChatML messages:

{
  "messages": [
    {"role": "system", "content": "You are Connor, ..."},
    {"role": "user", "content": "Explain quantum computing..."},
    {"role": "assistant", "content": "Quantum computing uses qubits..."}
  ],
  "quality": 5.0,
  "lang": "en",
  "source": "web_gold_v1"
}

Quality Certification

Every pair in this dataset has been certified at ≥ 5.0/5.0 using a proprietary quality scoring system. Scores reflect:

  • Technical density (citations, measurements, formulas)
  • Structural richness (step-by-step reasoning, examples)
  • Language diversity and authenticity
  • Vocabulary breadth and originality
  • Content coherence and depth

Access

This dataset is gated — commercial use requires a license.

For access:

  • Research / non-commercial: Contact for evaluation
  • Commercial license: Contact for pricing

License

connor-gold-v1 — Proprietary gold training data. Redistribution, reverse engineering of the quality pipeline, or sublicensing is prohibited.

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