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: ArrowInvalid
Message: Failed to parse string: '' as a scalar of type int64
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 2303, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2143, in cast_array_to_feature
return array_cast(
array,
...<2 lines>...
allow_decimal_to_str=allow_decimal_to_str,
)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2006, in array_cast
return array.cast(pa_type)
~~~~~~~~~~^^^^^^^^^
File "pyarrow/array.pxi", line 1147, in pyarrow.lib.Array.cast
File "/usr/local/lib/python3.14/site-packages/pyarrow/compute.py", line 412, in cast
return call_function("cast", [arr], options, memory_pool)
File "pyarrow/_compute.pyx", line 604, in pyarrow._compute.call_function
File "pyarrow/_compute.pyx", line 399, in pyarrow._compute.Function.call
result = GetResultValue(
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: Failed to parse string: '' as a scalar of type int64Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
quantbench-leaderboard-data
The complete measurement set behind the QuantBench leaderboard: 4-bit GPTQ and AWQ quantization of small instruct models, measured on rentable GPUs (NVIDIA A10 and T4).
271 rows — 237 ok, 34 failed. Failures are
published with their error strings rather than dropped.
Contents
rows.csv— 271 rows x 34 columns.rows/— one JSON per measured configuration.logs/—driver.log,heartbeat.txt,ledger.jsonfrom the runs.pools/BUILD.md— how to rebuild the calibration/eval pools. No corpus text is redistributed here; the recipe names the source datasets instead.
Coverage
- Models:
Qwen/Qwen2.5-1.5B-Instruct76,HuggingFaceTB/SmolLM2-1.7B-Instruct76,Qwen/Qwen2.5-3B-Instruct70,HuggingFaceTB/SmolLM3-3B37,deepgrove/Bonsai12 - Methods:
gptq146,awq108,none-fp1617 - GPU tiers:
A10141,T4130 - Calibration corpora (ok rows):
openhermes-2.5111,wikitext2-train110; sizes n=32/128/512, seeds 0-2.
Three caveats to read before quoting a number
- fp16 baselines are stack-specific. Each stack carries its own fp16 reference row measured under that stack's pinned torch/transformers versions, and they disagree: Qwen2.5-1.5B on A10 reads 45.38 tok/s on the AWQ stack vs 35.52 on the GPTQ stack — same weights, same GPU, identical perplexity (9.6394). Any speedup claim must name its stack. The effect is not uniform: it is +2.9% on SmolLM2/A10 and -3.6% on SmolLM2/T4, where the GPTQ stack is the faster one.
- 125 of 125 GPTQ rows loaded via
torch-fallback, a dequantize-in-PyTorch path rather than an optimized kernel. Thosetokens_per_secfigures are not an upper bound on GPTQ. webgpu_runnableis[UNVERIFIED]on every row andcolab_fitis avram_gb < 15threshold, not a Colab run.
Full protocol, numbered limitations and reproduction commands: https://quantbench.pages.dev/methodology.html
Exact quantized weights for the published configurations:
Mohaaxa/quantbench-artifacts.
Machine-generated benchmark output from an automated sweep; not human-verified row by row. A row that does not reproduce should be reported and will be marked or withdrawn.
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