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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:    CastError
Message:      Couldn't cast
status: string
schema: string
seq_len: int64
read_span_tokens: int64
packing_policy: string
target_policy: string
continuation_policy: string
padding_policy: string
attention_policy: string
shards: int64
raw_tokens: int64
windows: int64
samples_before_zero_filter: int64
filtered_zero_target_windows: int64
tool_segments: int64
tool_documents: int64
tool_document_tokens: int64
document_aligned_samples: int64
turn_aligned_continuations: int64
assistant_aligned_continuations: int64
hard_continuations: int64
padded_samples: int64
padded_tokens: int64
assistant_target_tokens: int64
packed_context_tokens: int64
valid_context_tokens: int64
coverage: double
valid_context_ratio: double
assistant_target_ratio: double
source_step: int64
model_tensor_count: int64
all_other_model_tensors_bitwise_identical: bool
source: string
new_embedding_32001_exact_expected_mean: bool
new_embedding_32000_exact_expected_mean: bool
intentionally_resized_tensor_count: int64
embedding_first_32000_rows_bitwise_identical: bool
converted_step: int64
intentionally_resized_tensors: list<item: string>
  child 0, item: string
sha256: string
token_roles_old_rows_identical_and_new_zero: bool
errors: list<item: null>
  child 0, item: null
converted: string
to
{'status': Value('string'), 'source': Value('string'), 'converted': Value('string'), 'source_step': Value('int64'), 'converted_step': Value('int64'), 'model_tensor_count': Value('int64'), 'intentionally_resized_tensor_count': Value('int64'), 'intentionally_resized_tensors': List(Value('string')), 'all_other_model_tensors_bitwise_identical': Value('bool'), 'embedding_first_32000_rows_bitwise_identical': Value('bool'), 'new_embedding_32000_exact_expected_mean': Value('bool'), 'new_embedding_32001_exact_expected_mean': Value('bool'), 'token_roles_old_rows_identical_and_new_zero': Value('bool'), 'sha256': Value('string'), 'errors': List(Value('null'))}
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
              status: string
              schema: string
              seq_len: int64
              read_span_tokens: int64
              packing_policy: string
              target_policy: string
              continuation_policy: string
              padding_policy: string
              attention_policy: string
              shards: int64
              raw_tokens: int64
              windows: int64
              samples_before_zero_filter: int64
              filtered_zero_target_windows: int64
              tool_segments: int64
              tool_documents: int64
              tool_document_tokens: int64
              document_aligned_samples: int64
              turn_aligned_continuations: int64
              assistant_aligned_continuations: int64
              hard_continuations: int64
              padded_samples: int64
              padded_tokens: int64
              assistant_target_tokens: int64
              packed_context_tokens: int64
              valid_context_tokens: int64
              coverage: double
              valid_context_ratio: double
              assistant_target_ratio: double
              source_step: int64
              model_tensor_count: int64
              all_other_model_tensors_bitwise_identical: bool
              source: string
              new_embedding_32001_exact_expected_mean: bool
              new_embedding_32000_exact_expected_mean: bool
              intentionally_resized_tensor_count: int64
              embedding_first_32000_rows_bitwise_identical: bool
              converted_step: int64
              intentionally_resized_tensors: list<item: string>
                child 0, item: string
              sha256: string
              token_roles_old_rows_identical_and_new_zero: bool
              errors: list<item: null>
                child 0, item: null
              converted: string
              to
              {'status': Value('string'), 'source': Value('string'), 'converted': Value('string'), 'source_step': Value('int64'), 'converted_step': Value('int64'), 'model_tensor_count': Value('int64'), 'intentionally_resized_tensor_count': Value('int64'), 'intentionally_resized_tensors': List(Value('string')), 'all_other_model_tensors_bitwise_identical': Value('bool'), 'embedding_first_32000_rows_bitwise_identical': Value('bool'), 'new_embedding_32000_exact_expected_mean': Value('bool'), 'new_embedding_32001_exact_expected_mean': Value('bool'), 'token_roles_old_rows_identical_and_new_zero': Value('bool'), 'sha256': Value('string'), 'errors': List(Value('null'))}
              because column names don't match

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final_sft_corrected

MercanAI Türkçe SFT corpusunun doğrulanmış final corrected snapshot'ı.

  • 22.870.823 doküman
  • 51.789.493 mesaj
  • 5.600.853.518 pretokenized token
  • 3.052.594.221 assistant-trainable token
  • 108 shard
  • normalized duplicate: 0
  • max single message: 8188 token
  • final verify: PASS

Detaylı veri lineage'ı, kaynak/kategori dağılımları, temizleme politikası, 8K packing, 5B-token SFT eğitim konfigürasyonu ve evaluation sonuçları için TECHNICAL_REPORT.md dosyasına bakın.

Upstream kaynaklar farklı lisans ve kullanım koşullarına sahip olabilir; bu repo tüm upstream içeriği tek bir lisans altında yeniden lisanslama beyanı değildir.

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