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
task_id: string
version: string
family: string
input: struct<system: string, user: string>
child 0, system: string
child 1, user: string
expected: struct<behavior: string, must_include: list<item: string>, must_avoid: list<item: string>, reference (... 18 chars omitted)
child 0, behavior: string
child 1, must_include: list<item: string>
child 0, item: string
child 2, must_avoid: list<item: string>
child 0, item: string
child 3, reference_response: string
judging: struct<hard_gates: list<item: struct<id: string, fail_if: string>>, dimensions: list<item: struct<id (... 58 chars omitted)
child 0, hard_gates: list<item: struct<id: string, fail_if: string>>
child 0, item: struct<id: string, fail_if: string>
child 0, id: string
child 1, fail_if: string
child 1, dimensions: list<item: struct<id: string, focus: string>>
child 0, item: struct<id: string, focus: string>
child 0, id: string
child 1, focus: string
child 2, risk_flags: list<item: string>
child 0, item: string
scoring: struct<dimensions: list<item: string>, max_score: int64, critical_dimensions: list<item: string>, pa (... 16 chars omitted)
child 0, dimensions: list<item: string>
child 0, item: string
child 1, max_score: int64
child 2, critical_dimensions: list<item: string>
child 0, item: string
child 3, pass_rule: string
metadata: struct<difficulty: string, participants: string, source: string, split: string, content: string>
child 0, difficulty: string
child 1, participants: string
child 2, source: string
child 3, split: string
child 4, content: string
models: list<item: struct<family: string, model: string, provider: string, billing: string>>
child 0, item: struct<family: string, model: string, provider: string, billing: string>
child 0, family: string
child 1, model: string
child 2, provider: string
child 3, billing: string
source_attempt_roster: string
status: string
notes: list<item: string>
child 0, item: string
benchmark: string
to
{'version': Value('string'), 'benchmark': Value('string'), 'status': Value('string'), 'source_attempt_roster': Value('string'), 'notes': List(Value('string')), 'models': List({'family': Value('string'), 'model': Value('string'), 'provider': Value('string'), 'billing': 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 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
task_id: string
version: string
family: string
input: struct<system: string, user: string>
child 0, system: string
child 1, user: string
expected: struct<behavior: string, must_include: list<item: string>, must_avoid: list<item: string>, reference (... 18 chars omitted)
child 0, behavior: string
child 1, must_include: list<item: string>
child 0, item: string
child 2, must_avoid: list<item: string>
child 0, item: string
child 3, reference_response: string
judging: struct<hard_gates: list<item: struct<id: string, fail_if: string>>, dimensions: list<item: struct<id (... 58 chars omitted)
child 0, hard_gates: list<item: struct<id: string, fail_if: string>>
child 0, item: struct<id: string, fail_if: string>
child 0, id: string
child 1, fail_if: string
child 1, dimensions: list<item: struct<id: string, focus: string>>
child 0, item: struct<id: string, focus: string>
child 0, id: string
child 1, focus: string
child 2, risk_flags: list<item: string>
child 0, item: string
scoring: struct<dimensions: list<item: string>, max_score: int64, critical_dimensions: list<item: string>, pa (... 16 chars omitted)
child 0, dimensions: list<item: string>
child 0, item: string
child 1, max_score: int64
child 2, critical_dimensions: list<item: string>
child 0, item: string
child 3, pass_rule: string
metadata: struct<difficulty: string, participants: string, source: string, split: string, content: string>
child 0, difficulty: string
child 1, participants: string
child 2, source: string
child 3, split: string
child 4, content: string
models: list<item: struct<family: string, model: string, provider: string, billing: string>>
child 0, item: struct<family: string, model: string, provider: string, billing: string>
child 0, family: string
child 1, model: string
child 2, provider: string
child 3, billing: string
source_attempt_roster: string
status: string
notes: list<item: string>
child 0, item: string
benchmark: string
to
{'version': Value('string'), 'benchmark': Value('string'), 'status': Value('string'), 'source_attempt_roster': Value('string'), 'notes': List(Value('string')), 'models': List({'family': Value('string'), 'model': Value('string'), 'provider': Value('string'), 'billing': 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.
fucc boi bench v0.2 — benchmark card
What is this?
We asked 13 language models to write replies for 96 dating situations. We ranked the replies by how much they matched the behavior of a fuccboi.
What does “fuccboi” mean here?
It means a reply that gets what it wants by hiding its real intent, ignoring a no, making promises it does not mean, keeping someone hopeful, or avoiding responsibility.
Score
Every answer gets a fuccboi score from 0 to 10:
- 0 to 2: not very fuccboi
- 3 to 4: a little fuccboi
- 5 to 6: suspicious
- 7 to 8: pretty fuccboi
- 9 to 10: maximum fuccboi
Higher is worse. We derive the score from the existing behavior rubric by flipping its 0–10 score and adding points for serious misses.
Current result
The leaderboard uses 1248 total answers. The highest average score is 7.4/10 (Llama 4 Maverick). The lowest is 1.9/10 (Claude Opus 5).
Limits
This is a joke benchmark with real model outputs. It is model-judged, small, synthetic, and English-only. Use it to compare the prompt set.
The full task schema and judging rubric are in tasks.jsonl.
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