The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
fan_id: string
turn_idx: int64
fan_context: string
model_output: string
real_kassyy_response: string
spend_tier: string
events: list<item: null>
child 0, item: null
context_messages: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
latency_s: double
error: null
must_include_any: list<item: string>
child 0, item: string
notes: string
prompt_id: string
severity: string
category: string
must_not_include_any: list<item: string>
child 0, item: string
prior_turns: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
fan_message: string
to
{'prompt_id': Value('string'), 'category': Value('string'), 'severity': Value('string'), 'fan_message': Value('string'), 'prior_turns': List({'role': Value('string'), 'content': Value('string')}), 'must_include_any': List(Value('string')), 'must_not_include_any': List(Value('string')), 'notes': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 295, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2281, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2227, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
fan_id: string
turn_idx: int64
fan_context: string
model_output: string
real_kassyy_response: string
spend_tier: string
events: list<item: null>
child 0, item: null
context_messages: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
latency_s: double
error: null
must_include_any: list<item: string>
child 0, item: string
notes: string
prompt_id: string
severity: string
category: string
must_not_include_any: list<item: string>
child 0, item: string
prior_turns: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
fan_message: string
to
{'prompt_id': Value('string'), 'category': Value('string'), 'severity': Value('string'), 'fan_message': Value('string'), 'prior_turns': List({'role': Value('string'), 'content': Value('string')}), 'must_include_any': List(Value('string')), 'must_not_include_any': List(Value('string')), 'notes': 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.
YAML Metadata Warning:The task_categories "conversational" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Kassyy Chatter v2 — SFT Dataset
Multi-turn CoT training data for an OnlyFans chatter agent, distilled from ~1,300 real fan conversations.
Files
train_cot.jsonl— 8,641 training windows (200-turn rolling windows, stride 50)val_cot.jsonl— 614 validation windowsdataset_meta.json— split stats + tier/persona distributionchat_summaries.json— per-chat summary briefs (WHO/SPEND/VIBE/WORKS/AVOID/...) injected into system promptssafety_training_records.jsonl— 1,351 synthesized safety/redirect examples (518 mixed into train at 6%)safety_synthesized.jsonl/safety_labeled_opus.jsonl— synthesis + classifier artifactsaxolotl_config.yaml— training config (Hermes-3-70B LoRA on 8xB200, seq_len 24576, 20+ special tokens)
Special tokens
- CoT:
<think>,</think> - Chatter actions:
<send_ppv,<send_pic>,<send_vid>,<send_voice>,<send_gif>,<send_free - Observations:
<ppv_opened,<ppv_unopened,<tip_received,<fan_sent_pic>,<fan_sent_vid>,<fan_sent_voice>,<fan_sent_gif> - State:
<script_active=,<scripts_available=,<cooling=,<exhausted=
Canonical slot vocabulary
Creator-agnostic slot names that map to each creator's own vault:
free_pic_1, free_pic_2, free_vid, paid_vid_1..7, extra_pic, extra_vid, custom
Notes
- No tier/revenue label in system prompt — model must infer from conversation
- Cross-persona name scrub applied (13 persona variants during training)
- Mid-sexual-start records filtered (~1,500 dropped)
- 6h script cooling rule, last-slot-in-selling-order = exhausted
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