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
id: string
index: int64
response: string
reasoning: string
finish_reason: string
usage: struct<completion_tokens: int64, prompt_tokens: int64, total_tokens: int64, prompt_tokens_details: s (... 28 chars omitted)
child 0, completion_tokens: int64
child 1, prompt_tokens: int64
child 2, total_tokens: int64
child 3, prompt_tokens_details: struct<cached_tokens: int64>
child 0, cached_tokens: int64
elapsed_s: double
tokens_per_second: double
domain: string
source: string
messages: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
to
{'messages': List({'role': Value('string'), 'content': Value('string')}), 'source': Value('string'), 'domain': Value('string'), 'id': 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
id: string
index: int64
response: string
reasoning: string
finish_reason: string
usage: struct<completion_tokens: int64, prompt_tokens: int64, total_tokens: int64, prompt_tokens_details: s (... 28 chars omitted)
child 0, completion_tokens: int64
child 1, prompt_tokens: int64
child 2, total_tokens: int64
child 3, prompt_tokens_details: struct<cached_tokens: int64>
child 0, cached_tokens: int64
elapsed_s: double
tokens_per_second: double
domain: string
source: string
messages: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
to
{'messages': List({'role': Value('string'), 'content': Value('string')}), 'source': Value('string'), 'domain': Value('string'), 'id': 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.
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moe-40b-a18b-dataset
Training data for Leonther/moe-40b-a18b-lora — an experimental 40B-A18B MoE
student distilled from GLM-5.3-Flash.
Composition
| file | records | source | description |
|---|---|---|---|
gold/professor.jsonl |
2 | GLM-5.3-Flash (local, ~2 t/s) | gold question/answer pairs |
gold/professor_raw.jsonl |
2 | GLM-5.3-Flash | raw batch output (ids, usage) |
gold/seeds.jsonl |
22 | qwen38 | professor prompt seeds (domain + length bucket) |
fake/synthetic.jsonl |
100 | qwen38 (Qwen3.8-27B TURBO) | synthetic imitation in GLM-5.3 style |
fake/synthetic_raw.jsonl |
100 | qwen38 | raw batch output |
Answer lengths were requested as short (≤256 tok), medium (≤512), long
(≤1024); the goal was a length-diverse SFT set.
Excluded on purpose: local agent/user chat traces used in the mix (private).
Format
JSONL, one object per line:
{"messages": [{"role": "system", "content": "..."},
{"role": "user", "content": "..."},
{"role": "assistant", "content": "..."}],
"source": "professor:glm53 | synthetic:qwen38",
"domain": "reasoning | mathematics | coding | ...",
"length": "short | medium | long",
"id": "prof-0000"}
Notes
- Synthetic, experimental data; gold answers were generated by GLM-5.3-Flash running locally, fake data by qwen38 imitating its style.
- Small on purpose (one-day run). The observed student overfitting is caused by this small SFT set; scale it up for further training.
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