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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
depth: int64
blocks: int64
per_position_conditional: list<item: double>
child 0, item: double
per_position_prefix: list<item: double>
child 0, item: double
mean_accepted_length: double
mean_accepted_length_check: double
label: string
convention: string
per_token_acceptance: double
per_position_acceptance: list<item: double>
child 0, item: double
predicted_tok_s_V0: double
predicted_tok_s_V296: double
dtype: string
aux_layers: list<item: int64>
child 0, item: int64
texts_consumed: int64
shards: list<item: struct<file: string, tokens: int64, samples: int64>>
child 0, item: struct<file: string, tokens: int64, samples: int64>
child 0, file: string
child 1, tokens: int64
child 2, samples: int64
model: string
hidden: int64
storage: string
aux_tap: string
to
{'aux_layers': List(Value('int64')), 'hidden': Value('int64'), 'dtype': Value('string'), 'storage': Value('string'), 'aux_tap': Value('string'), 'model': Value('string'), 'texts_consumed': Value('int64'), 'shards': List({'file': Value('string'), 'tokens': Value('int64'), 'samples': Value('int64')})}
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
depth: int64
blocks: int64
per_position_conditional: list<item: double>
child 0, item: double
per_position_prefix: list<item: double>
child 0, item: double
mean_accepted_length: double
mean_accepted_length_check: double
label: string
convention: string
per_token_acceptance: double
per_position_acceptance: list<item: double>
child 0, item: double
predicted_tok_s_V0: double
predicted_tok_s_V296: double
dtype: string
aux_layers: list<item: int64>
child 0, item: int64
texts_consumed: int64
shards: list<item: struct<file: string, tokens: int64, samples: int64>>
child 0, item: struct<file: string, tokens: int64, samples: int64>
child 0, file: string
child 1, tokens: int64
child 2, samples: int64
model: string
hidden: int64
storage: string
aux_tap: string
to
{'aux_layers': List(Value('int64')), 'hidden': Value('int64'), 'dtype': Value('string'), 'storage': Value('string'), 'aux_tap': Value('string'), 'model': Value('string'), 'texts_consumed': Value('int64'), 'shards': List({'file': Value('string'), 'tokens': Value('int64'), 'samples': Value('int64')})}
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.
GLM-5.3-Flash speculative-decoding drafter training data (slice B)
Hidden-state extraction from the AWQ W4A16 target wtdcode/GLM-5.3-Flash-AWQ-W4A16 (base zai-org/GLM-5.3-Flash, MIT) for training DFlash2-layout drafters.
- sliceB/: 9 shards, 455,367 tokens, aux taps [5,14,24,33,42], tap hc_post-materialized+stream-mean, int16 bit-views of bf16; corpora HuggingFaceH4/ultrachat_200k (MIT), allenai/tulu-3-sft-mixture (ODC-BY).
- target-shared.safetensors: the target embed_tokens and lm_head (bf16), frozen in training.
- specdec-tools-eb1434a8.tar.gz: tools from PixelML/sm80vllm branch specdec/glm5next-aux-hidden-states @ eb1434a8 (Apache-2.0). Published by Pixel ML for the club-170hx drafter lane. No third-party drafter weights are included.
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