The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Own your inference — benchmark data
Raw benchmark artifacts behind the "own your inference" talk: what a self-hosted GLM-5.2 endpoint can and cannot do, measured on three deployments.
Companion code repository: Gladiator07/own-your-inference. It holds the runners that produced this data and a script that rebuilds every table from these artifacts on a laptop.
The three deployments
| Experiment | Hardware | Weights | KV cache |
|---|---|---|---|
h200-fp8-kv |
8x NVIDIA H200 | GLM-5.2 FP8 | fp8_e4m3 |
h200-bf16-kv |
8x NVIDIA H200 | GLM-5.2 FP8 | bfloat16 |
blackwell-nvfp4 |
8x NVIDIA RTX PRO 6000 Blackwell | GLM-5.2 NVFP4 | fp8_e4m3 |
Layout
| Path | Contents |
|---|---|
compact/ |
small download: result tables rebuilt from the raw artifacts, quality tables, and reconciled summaries |
hammer/<experiment>/ |
closed-loop capacity sweeps: N sessions sending nonstop |
paced/<experiment>/ |
open-loop capacity sweeps: sessions arrive on a recorded developer rhythm |
quality/<experiment>/ |
Terminal-Bench 2.1 runs through the pinned Terminus-2 agent |
deployment/blackwell-nvfp4/ |
server bringup evidence for the Blackwell deployment |
inputs/ |
the replay corpora and arrival rhythm; SOURCES.md says where they come from |
Every experiment folder has a meta.json with the server identity, inputs, parameters, and headline numbers. Start there.
Capacity sweep logs sit beside their folders (for example hammer/h200-bf16-kv.log). A paced curve that spans two server boots keeps one folder per boot (boot-a/, boot-b/); the boot split is described in that experiment's meta.json.
Integrity
MANIFEST.jsonl lists every artifact file with its size and SHA-256. SHA256SUMS is the same list in plain checksum format.
Talk
Deck: share.atharvaingle.dev/dhs-2026
License
CC-BY-4.0. The replay corpora are derived from the LMCache agentic traces (CC-BY-4.0); inputs/SOURCES.md has the details.
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