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
repo_id: string
repo_type: string
created_at: string
model_source: struct<repo_id: string, revision: string>
child 0, repo_id: string
child 1, revision: string
total_size_bytes: int64
files: list<item: struct<path: string, size_bytes: int64, sha256: string>>
child 0, item: struct<path: string, size_bytes: int64, sha256: string>
child 0, path: string
child 1, size_bytes: int64
child 2, sha256: string
source_platform: string
source_environment: string
sha256: string
size_bytes: int64
built_at: string
torch: string
archive: string
torch_cuda: string
python: string
to
{'archive': Value('string'), 'sha256': Value('string'), 'size_bytes': Value('int64'), 'source_environment': Value('string'), 'built_at': Value('string'), 'source_platform': Value('string'), 'python': Value('string'), 'torch': Value('string'), 'torch_cuda': 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 478, 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 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
repo_id: string
repo_type: string
created_at: string
model_source: struct<repo_id: string, revision: string>
child 0, repo_id: string
child 1, revision: string
total_size_bytes: int64
files: list<item: struct<path: string, size_bytes: int64, sha256: string>>
child 0, item: struct<path: string, size_bytes: int64, sha256: string>
child 0, path: string
child 1, size_bytes: int64
child 2, sha256: string
source_platform: string
source_environment: string
sha256: string
size_bytes: int64
built_at: string
torch: string
archive: string
torch_cuda: string
python: string
to
{'archive': Value('string'), 'sha256': Value('string'), 'size_bytes': Value('int64'), 'source_environment': Value('string'), 'built_at': Value('string'), 'source_platform': Value('string'), 'python': Value('string'), 'torch': Value('string'), 'torch_cuda': 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.
OPD Research 复现资产
本仓库集中保存 zhongzero/OPD_research GitHub 项目无法直接提交的大文件。源码、复现脚本和完整教程位于：
https://github.com/zhongzero/OPD_research
内容
conda/opsd-conda-linux-x86_64.tar.zst：已经解包验证的 OPSD conda 环境，Python 3.10.20、PyTorch 2.8.0+cu128、CUDA runtime 12.8。models/Qwen3-1.7B/：Qwen/Qwen3-1.7Brevision70d244cc86ccca08cf5af4e1e306ecf908b1ad5e的完整本地 snapshot。datasets/opsd-hf-datasets-cache.tar.zst：训练数据和 AIME24、AIME25、HMMT25 的最小离线 Hugging Face cache。manifests/SHA256SUMS：本仓库所有环境、模型和数据资产的逐文件 SHA-256。manifests/assets.manifest.json：来源、大小和校验值的结构化 manifest。
Qwen3-1.7B 保留原模型附带的 Apache 2.0 LICENSE。conda 环境内各依赖继续遵循各自许可证，因此整个混合资产仓库标记为 other。
下载
安装 Hugging Face CLI 后下载全部资产：
hf download zhongzero/OPD_research \
--repo-type dataset \
--local-dir /PATH/TO/OPD_research/hf_assets
校验：
cd /PATH/TO/OPD_research/hf_assets
sha256sum --check manifests/SHA256SUMS
目标服务器无法连接 Hugging Face 时，在可联网机器完成上述下载，再将整个 hf_assets/ 目录手动
传到目标服务器的 OPD_research/hf_assets/。GitHub 仓库中的 bootstrap 和 bundle 脚本会在
本地校验通过时完全跳过网络访问，并自动解包环境与数据 cache。
跨服务器的 conda 解包、数据下载和 train/eval 步骤见 GitHub 仓库根目录 README.md。
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