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Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1531, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1405, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 982, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
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/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1393, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1571, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
tar unknown | __key__ string | __url__ string |
|---|---|---|
"YmluAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA(...TRUNCATED) | 073ec47a8c22dcaa4d6e5758799ccefe2f9bde943685830b1bf6fd2395f5eabc | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
"YXBwLwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA(...TRUNCATED) | e54d39dd357723fa47bd55e1fcadadd4e4882e84f0c323ad63413edd1a650020 | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
"ZXRjLwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA(...TRUNCATED) | 4301ca2582783d1e24d10a36f7d8196f2be58370b25f12b94a099f3d19e3af84 | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
"YXBwLwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA(...TRUNCATED) | ee239e6b556fc7f74a74a4b74137119b5812aac4caa267dc447ac5feafef107e | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
"YXBwLwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA(...TRUNCATED) | a774598c97ec78aa60b578e3f9f5e074c68a93c4d465117607a95e5bda435a0b | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
null | 64b43d0dbddfbc0291d03486954c3def53d5d19c67426c8f758631d5dd9d7d85 | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
null | manifest | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
"Li8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA(...TRUNCATED) | eb5f13bce9936c760b9fa73aeb1b608787daa36106cc888104132e353ed37252 | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
"ZXRjLwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA(...TRUNCATED) | 2a9c7b727490d026db269bdf2bf74ce80e17abe26fc4dd99bd53b3d1686e58dc | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
"ZXRjLwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA(...TRUNCATED) | 1ce62254e2a41ba52d6f4edab1c02c6733a219d0b27ff7b0d495f2987fc165ad | "hf://datasets/daixuancheng/terminal-bench-2.1@f6d6fabc9c87c82c099559e96e958478ff124c27/tb21/7131e43(...TRUNCATED) |
Terminal Bench 2.1
A versioned mirror of the 89 official Terminal Bench 2.1 tasks and their 89 Linux amd64 container images. The task source is pinned to 7131e4375048a0e408a8fb404b5f499d726b695b. The image archives total approximately 19.31 GiB.
Download
A compatible runner can download the task archive and manifests first, then fetch only the image archives required by its selected tasks. No Hugging Face token or private-repository access is required for downloads.
hf download daixuancheng/terminal-bench-2.1 \
release-manifest.json SHA256SUMS \
tb21/7131e437/tasks.tar.gz \
tb21/7131e437/tasks-manifest.json \
tb21/7131e437/images/manifest.json \
--repo-type dataset --local-dir ./terminal-bench-2.1
Pin the dataset commit when using this release in an experiment.
The task manifest maps tasks to image references. Each image manifest record
contains its archive filename, SHA-256, expected image ID, original registry
digest, and platform. Download the matching
tb21/7131e437/images/<archive> file, verify its SHA-256, and import it with:
docker load --input /path/to/image.tar.gz
# Or:
podman load --input /path/to/image.tar.gz
The image archive is fetched from this Hugging Face dataset. Container startup must use the imported local image without pulling from its original registry.
Contents
| Path | Contents |
|---|---|
tb21/7131e437/tasks.tar.gz |
Official task files, reference solutions, tests, README, and license |
tb21/7131e437/tasks-manifest.json |
Task paths, image references, task limits, and task-file checksums |
tb21/7131e437/images/ |
89 original image archives and their manifest |
tb21/7131e437/verifier-apt/v1/ |
8 pinned verifier APT packages and their manifest |
tb21/7131e437/fixtures/ |
2 checksum-pinned static test resources and source attribution |
release-manifest.json |
Complete file inventory with sizes and SHA-256 values |
SHA256SUMS |
File checksums for download verification |
The task archive already contains the selected complete official task set. Consumers do not need to filter tasks or rebuild the images.
Runtime requirements
Use a compatible Linux amd64 Docker or Podman environment and a task runner. This release supplies task assets and selected verifier dependencies. A full offline Python environment, all system packages, a model runner, and all verifier dependency caches are not included. Those components must be installed or prepared separately before running on a restricted network.
The static fixture sources are recorded for attribution; use their packaged copies on machines without general internet access.
Licensing and benchmark integrity
Task source is distributed under the upstream Apache-2.0 license in
licenses/terminal-bench-2-1-LICENSE. Container images retain their upstream
software notices and component licenses. Preserve those notices when
redistributing the artifacts.
Reference solutions and benchmark canary notices are preserved from the upstream task source. Results on tasks used for training are training-set results, not held-out benchmark scores.
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