Dataset Viewer
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
dosya: string
kayit: int64
bayt: int64
sha256: string
parca: int64
dogrulama: string
tarif: string
donanim: string
ayar: string
uretici: string
degerlendirici: string
puan: string
sonuc: string
kitap: string
syzygy: string
egitim_notu: string
to
{'dosya': Value('string'), 'kayit': Value('int64'), 'bayt': Value('int64'), 'sha256': Value('string'), 'parca': Value('int64'), 'dogrulama': Value('string'), 'uretici': Value('string'), 'degerlendirici': Value('string'), 'puan': Value('string'), 'sonuc': Value('string'), 'syzygy': Value('string'), 'kitap': Value('string'), 'ayar': Value('string'), 'donanim': Value('string'), 'egitim_notu': 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 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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
dosya: string
kayit: int64
bayt: int64
sha256: string
parca: int64
dogrulama: string
tarif: string
donanim: string
ayar: string
uretici: string
degerlendirici: string
puan: string
sonuc: string
kitap: string
syzygy: string
egitim_notu: string
to
{'dosya': Value('string'), 'kayit': Value('int64'), 'bayt': Value('int64'), 'sha256': Value('string'), 'parca': Value('int64'), 'dogrulama': Value('string'), 'uretici': Value('string'), 'degerlendirici': Value('string'), 'puan': Value('string'), 'sonuc': Value('string'), 'syzygy': Value('string'), 'kitap': Value('string'), 'ayar': Value('string'), 'donanim': Value('string'), 'egitim_notu': Value('string')}
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.
The data here seems good enough on its own to train a pretty strong NNUE. In my own tests it did a good job of pulling draws out of Stockfish :P To keep costs down, it was relabeled with t1-256x10-rl-base-swa-3860000, and most of the self-play games were also generated with that same model, in a single pass with a bit of temperature. Bigger lc0 models would be far more effective, but this one hit around 660k/s on 8× 5090s, which made it cheap, so that's what I went with.
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