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:    ValueError
Message:      Expected object or value
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Column(/ranges/[]/layout) changed from object to array in row 0
              
              During handling of the above exception, another exception occurred:
              
              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 304, in _generate_tables
                  batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
                  examples = [ujson_loads(line) for line in original_batch.splitlines()]
                              ~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
                  return pd.io.json.ujson_loads(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value

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.

Flychess Stockfish 500k

A reproducible, sharded dataset of 500,000 legal chess positions with Stockfish depth-3 move and bounded value labels for training and evaluating Flychess FlyNet.

This repository is the canonical 500k dataset release. It contains binary training shards, integrity sidecars, a machine-readable manifest, and the schema files needed to interpret the arrays without guessing.

Release identity

  • Dataset: Flychess Stockfish 500k
  • Canonical release prefix: campaign/depth3/segment-000-500k-fresh-20260921
  • Samples: 500,000
  • Shards: 5 x 100,000 positions
  • Feature width: 851
  • Action vocabulary: 4,544 deterministic UCI move shapes
  • Teacher: Stockfish, depth 3
  • Position sampler: uniform_legal_playout_per_global_index
  • Plies per sampled position: 4-60
  • Generation seed: 20260921
  • Source commit: 1efceab534244096b9af309262913abdf0be2982
  • Schema version: flynet.sharded_dataset/v1

The manifest is authoritative for exact counts, shard boundaries, checksums, and provenance. The three schema files in the release prefix are authoritative for array interpretation.

Repository layout

campaign/depth3/segment-000-500k-fresh-20260921/
|- manifest.json
|- feature-schema.json
|- label-schema.json
|- action-vocabulary.json
|- shard-000000.npz
|- shard-000000.json
|- ...
|- shard-000004.npz
|- shard-000004.json

Each NPZ shard contains four arrays:

Array Shape Stored dtype Meaning
features [N, 851] float16 FlyNet board encoding
action_indices [N] uint16 Index into action-vocabulary.json
values [N] float16 Bounded side-to-move teacher value in [-1, 1]
fens [N] Unicode string Exact FEN for the sampled position

The per-shard JSON sidecar records the sample range, byte count, storage contract, and SHA-256 digest for the corresponding NPZ file.

Loading a shard

Use allow_pickle=False when reading the files:

from pathlib import Path
import numpy as np
from huggingface_hub import snapshot_download

repo_id = "YOUR_HF_NAMESPACE/flychess-stockfish-500k"
prefix = "campaign/depth3/segment-000-500k-fresh-20260921"

root = Path(snapshot_download(
    repo_id=repo_id,
    repo_type="dataset",
    allow_patterns=[f"{prefix}/*"],
))

with np.load(root / prefix / "shard-000000.npz", allow_pickle=False) as shard:
    features = shard["features"]
    action_indices = shard["action_indices"]
    values = shard["values"]
    fens = shard["fens"]

print(features.shape, action_indices.shape, values.shape, fens.shape)

The source project provides the compatible FlyNet encoder and training loader. The schema files make the storage contract independently inspectable.

Feature contract

The 851 features are ordered as follows:

  1. 768 piece-square indicators: white then black, six piece types, 64 squares.
  2. One side-to-move scalar: +1 for White and -1 for Black.
  3. Four castling-right indicators.
  4. A 64-element en-passant-square one-hot region.
  5. Halfmove and fullmove counters with the documented clipping and scaling.
  6. Twelve normalized piece-count features.

See feature-schema.json for exact half-open index ranges and semantics.

Provenance and limitations

  • Positions are generated from legal chess playouts; they are not human game records.
  • Stockfish supplies the move and bounded value labels. Depth 3 is a low-cost teacher setting, not ground truth or a claim of playing strength.
  • This release is a versioned publication of a verified 500,000-position snapshot. The manifest records the source prefix and source commit; the upload itself does not claim that all positions were newly generated during publication.
  • The data encodes the FlyNet feature contract. It is an engineering dataset, not a biological connectome or evidence of biological cognition.
  • The dataset is stored as NumPy NPZ rather than Apache Arrow/Parquet, so the full feature arrays are intended for programmatic loading rather than automatic row preview in the Hub Dataset Viewer.

Licensing and attribution

The dataset contains generated labels produced with Stockfish; it does not redistribute Stockfish source code or a Stockfish binary. Stockfish is distributed under GPLv3. Review the upstream Stockfish license and the Flychess source provenance before redistributing or incorporating this dataset into another release.

No broad permissive license is asserted for this generated artifact beyond the applicable third-party terms and the provenance recorded in manifest.json.

Downloads last month
240