Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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 136, in _cast_table
pa_table = table_cast(pa_table, 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 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2118, in cast_array_to_feature
casted_array_values = _c(array.values, feature.feature)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2068, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2071, in cast_array_to_feature
return pa.StructArray.from_arrays(arrays, names=list(feature), mask=array.is_null())
~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/array.pxi", line 4386, in pyarrow.lib.StructArray.from_arrays
File "pyarrow/array.pxi", line 1877, in pyarrow.lib.Array.validate
check_status(self.ap.Validate())
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Struct child array #13 invalid: Invalid: Length spanned by list offsets (1720) larger than values array (length 1716)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
Stockfish-augmented chess puzzle SFT data (option type 1)
Chain-of-thought SFT data for chess puzzles in which the thinking block lists the puzzle's solution line together with a few Stockfish alternative lines, in shuffled order, followed by the complete puzzle solution. Each record also carries the action-only (no CoT) target for the same puzzle.
- Puzzles: 79,306 (every usable row of
training_splits_v4/sft_dataset.csv), ratings 800–2199 - Files: 184 shards of 500 CSV rows,
sf_d16_mpv8_tempt3_max5_min2_r0123_cutrandom_seed0/datapuzzle_v4_shard{start}-{end}.json(360 MB) - Engine: Stockfish, depth 16, single thread, top-8 lines, hash cleared per puzzle (deterministic)
Fields used for training
| Format | Field (cot_field) |
|---|---|
| CoT, no labels (main) | cot_by_method.sf_multipv.cot_format_no_labels |
| CoT, each line tagged with Stockfish's bucketed eval | cot_by_method.sf_multipv.cot_format |
| Action-only (no CoT) | cot_by_method.solution_continuation.cot_format |
The prompt is pgn (the game up to and including the opponent's trigger move),
identical to the existing puzzle-sequence SFT data. Both targets contain the
complete puzzle solution in multi-turn form (move <call_env> reply move <call_env> …);
there is no 4-move cap.
Example (cot_format_no_labels):
<T> Pa2a3 Bb4d6 Ra1e1 <sep> Ra1e1 Pe6e5 Pc2c3 <sep> Bc4xe6 Nf6e4 Ng5xe4 <sep> Pc2c3 Bb4d6 Bf4xd6
<sep> Qf3xc6+ Pb7xc6 Bc4a6# <sep> Ng5xe6 Nf6e4 Ne6xd8 </T> Qf3xc6+ <call_env> Pb7xc6 Bc4a6# <call_env>
Generation rule
- Solution line: the puzzle's own moves, extended with Stockfish's best continuation where more plies are needed.
- Alternatives: Stockfish's top-8 lines minus the solution move.
- Tempting alternatives: b_j = first ply at which the solution line is ahead of alternative j on material (solver's view, mate = ±100) at that ply and the next. Alternatives with b_j ≥ 3 (or never refuted) are tempting. Keep up to 5 tempting alternatives in engine order; if fewer than 2, top up with the best-ranked others.
- Cut points: a = min(puzzle solution length in plies, first ply at which the solution stably leads every chosen alternative). The solution line is cut at a + r and each alternative at a + its own r, with r drawn uniformly from {0, 1, 2, 3} and limited to how far the line can continue. If the solution line reaches mate, every line is cut at the same ply, so the mate line is never the odd-length one.
- Order: lines are shuffled per puzzle (seeded by puzzle index).
Checks on the generated data: a length-only guesser ("pick the shortest/longest line") does no better than chance; the solution's position among the lines is uniform; every record contains the complete puzzle.
Statistics
Lines per puzzle:
| Lines | Puzzles |
|---|---|
| 2 | 562 |
| 3 | 30,130 |
| 4 | 5,286 |
| 5 | 5,382 |
| 6 | 37,946 |
Puzzle solution length (plies, solver + replies):
| Plies | Puzzles |
|---|---|
| 1 | 8,552 |
| 3 | 36,664 |
| 5 | 26,956 |
| 7 | 5,756 |
| 9 | 1,128 |
| 11 | 250 |
Mean cut ply of the solution line: 4.42. Mean thinking length: 21.8 moves. Puzzles with a mating solution (shared cut): 23,073.
Notes
- Skipped rows: 12,300 CSV rows have no
ctx(game record) and 13 have a trigger move that is illegal in their game record; both are skipped, as in the existing SFT data. - Stockfish crash fallback: this Stockfish build occasionally crashes on a top-8 search of specific
positions. For those 10 puzzles the alternatives come from searching each legal move separately
(
sf_meta.multipv_fallback = true). 53 shards were written before this fallback existed; they contain no crashed puzzles but lack themultipv_fallbackandsummary.error_countsfields. - Metadata:
sf_metaholds every line in UCI, its engine rank and eval, the cut points (a, r, H, per-line lengths), and each alternative's b_j and tempting flag. - File selection: the SFT trainer picks files by sorting names alphabetically; with these shard names that gives scattered puzzle ranges, so pass an explicit file list when training on a subset.
Generation code is in code/.
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