Datasets:
The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
item_id: string
track: string
region_code: string
columns: list<item: string>
child 0, item: string
history: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
future_drivers: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
ask: string
asset_code: string
to
{'item_id': Value('string'), 'track': Value('string'), 'asset_code': Value('string'), 'columns': List(Value('string')), 'history': List(List(Value('float64'))), 'future_drivers': List(List(Value('int64'))), 'ask': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
item_id: string
track: string
region_code: string
columns: list<item: string>
child 0, item: string
history: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
future_drivers: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
ask: string
asset_code: string
to
{'item_id': Value('string'), 'track': Value('string'), 'asset_code': Value('string'), 'columns': List(Value('string')), 'history': List(List(Value('float64'))), 'future_drivers': List(List(Value('int64'))), 'ask': 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.
Frontier Forecasting Arena (FFA) — v0.1 (items only)
Anonymized, answer-free evaluation items for the Frontier Forecasting Arena, a historical-replay benchmark that measures forecasting skill with proper scoring rules and is designed so that memorization is measurable rather than assumed away.
This dataset contains the model-facing items only — no ground truth. Skill is verified by the maintainer against held-out truth. That split is the whole point: no real date, absolute level, station, or year ships to a model, so answers can't be looked up or memorized.
Contents
| File | Arm | Items | Unit |
|---|---|---|---|
energy/items.jsonl |
Energy load | 50 | 168h history + 24h future drivers → 24×(q10,q50,q90) |
synthetic/items.jsonl |
Synthetic (DGP) | 50 | contamination-proof floor |
kalshi/items.jsonl |
Kalshi weather | 50 | settled-market snapshot ladder |
crypto/items.jsonl |
Crypto | 50 | hourly panel → forward window |
stock/items.jsonl |
Stock | 50 | daily panel → forward window |
Each line is one JSON item with a compact columns + packed-row encoding.
How to run it
Use the FFA CLI (code: https://github.com/steves-brain/ffa-benchmark):
huggingface-cli download userr99/ffa-v0.1 --repo-type dataset --local-dir ffa-v0.1
ffa predict --dataset ffa-v0.1 --out submissions/<your-name> \
--provider openai-compatible --base-url http://localhost:11434/v1 \
--model <your-model> --harness Ollama --dataset-version v0.1
ffa predict never sees the answers. Send the resulting submission back (see
CONTRIBUTING-SUBMISSIONS.md in the GitHub repo) to be scored against private
truth and added to the leaderboard.
Scoring spine
CRPS for the continuous arms, Brier/log-loss for binary. Never a single blended skill number — skill is a per-arm vector; only calibration aggregates across arms.
License
See the repository for terms. Built from free public data (EIA, NOAA/NWS, Kalshi, public crypto/stock markets), anonymized.
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