Datasets:
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/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/webdataset/webdataset.py", line 84, in _split_generators
raise ValueError(
...<2 lines>...
)
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
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 68, 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.
ARB ML and data science raw corpus
Study and practice material for the ML and data science track of Applied RSI Bench (ARB): the DARE-bench, QRData and DSBio tasks. An ARB post-training agent gets this corpus read-only before its model is evaluated. It holds datasets to practice on, the three tasks' container images (to run analyses offline), and library and methodology documentation.
The corpus holds no held-out test case. Every dataset was checked against a private
index of the three benchmarks' test cases (511 questions, 1,092 test tables): a dataset is
refused if it carries a test dataset's identity or file, a whole test table (in any row
and column order), 20 % of a test table's distinct rows, or 2 of its distinctive columns.
Every text file, image layers included, was refused if it shares a 13-word run (at least
6 of the words with a letter) with a test question, or links to the sites of the three
textbooks that 86 of QRData's 155 test questions come from (OpenIntro Statistics,
Quantitative Social Science, Causal Inference for the Brave and True). DARE-bench folders keep only metadata.txt and the training table, never the
validation files, labels or questions.
| file | files | unpacked → archive | tree_sha256 |
|---|---|---|---|
L.tar.gz |
17,542 | 2.62 GB → 2.33 GB | 2d9bc63a53bd823eb6daf8605db3a3ecbc1c4cf2720f61a1e0996feddbc1344f |
L.tar.gz sha256: 484aafa5f7075cab0f4c9b8aaceaa32a81d11788eb9a74da285b3ced0ffa6ec9
What is inside
| folder | what | size |
|---|---|---|
docs/ |
documentation pages (with docs/PACKET.json and docs/README.md) (17,467 files) | 323.3 MB |
datasets/ |
16 datasets: original files, dataset.json, verification.json (64 files) | 74.8 MB |
images/ |
OCI image archives, catalog and recipes (9 files) | 2.22 GB |
datasets/<id>/data/: each dataset's original files, unchanged.dataset.jsongives the source, license, identities and each file's format and schema;verification.jsonwhich files loaded, and in which image.images/: the three tasks' environments as OCI archives (podman load -i images/<id>.oci.tar):dare-task(DARE-bench),dsgym-instance(QRData, from DSGym) anddsbio-task(DSBio), built for linux/amd64.catalog.jsonlists them. Each one read the datasets with no network:dsbio-taskall 32 files, the other two 30 (no h5py for the two.h5adfiles).docs/: 17,465 documentation pages as text, one folder per source host;docs/PACKET.jsongives each page's source URL. Python 3.11 and 3.12 and pandas 2.2.3 come from their documentation archives.
PACKET.json lists every file with its sha256 and size; tree_sha256 is the sha256 of
the sorted lines "{path} {sha256}\n". RELEASE.json and catalog.json record the
build inputs. RELEASE.json says ready: false with a list of pending checks: the
build tool always writes that, because it cannot certify a release by itself.
Use
hf download junlinw/arb-ml-data-science-data-packet L.tar.gz --repo-type dataset --revision <commit> --local-dir .
mkdir -p ml-data-science && tar -xzf L.tar.gz -C ml-data-science
ARB pins the exact commit it installs in the tasks' benchmark.toml.
Datasets and licenses
| id | title | license | source |
|---|---|---|---|
| dare-varshitanalluri-crop-price-prediction-dataset-reg | Crop Price Prediction Dataset | MIT | Kaggle varshitanalluri/crop-price-prediction-dataset via DARE-bench |
| dare-harshvir04-index-value-economic-dataset-reg | Index value (economic dataset) | MIT | Kaggle harshvir04/index-value-economic-dataset via DARE-bench |
| dare-vivianyfwang-capital-bike-share-2018-20218-reg | Capital Bike Share | CC0-1.0 | Kaggle vivianyfwang/capital-bike-share-2018-20218 via DARE-bench |
| dare-ahsan81-used-handheld-device-data-reg | Used Phones & Tablets Pricing Dataset | CC0-1.0 | Kaggle ahsan81/used-handheld-device-data via DARE-bench |
| dare-himanshu9648-crop-price-prediction-dataset-in-india-ts | Crop Price Prediction in India dataset | CC0-1.0 | Kaggle himanshu9648/crop-price-prediction-dataset-in-india via DARE-bench |
| dare-olegshpagin-visa-stock-price-prediction-dataset-ts | Visa Stock Price Prediction Dataset | CC0-1.0 | Kaggle olegshpagin/visa-stock-price-prediction-dataset via DARE-bench |
| dare-negmgh-google-2020-2025-stock-market-ts | Google 2020-2025 Stock Market | Apache-2.0 | Kaggle negmgh/google-2020-2025-stock-market via DARE-bench |
| dare-pranav941--world-food-wealth-bank-ts | 🍕Food Bank🏦of the World🌍 | CC0-1.0 | Kaggle pranav941/-world-food-wealth-bank via DARE-bench |
| dare-miadul-brain-tumor-dataset-class | Brain Tumor Dataset | MIT | Kaggle miadul/brain-tumor-dataset via DARE-bench |
| dare-ashishgup-netflix-rotten-tomatoes-metacritic-imdb-class | Latest Netflix data with 26+ joined attributes | CC0-1.0 | Kaggle ashishgup/netflix-rotten-tomatoes-metacritic-imdb via DARE-bench |
| dare-mexwell-image-sentiment-polarity-class | 🖼️ Image Sentiment Polarity | CC0-1.0 | Kaggle mexwell/image-sentiment-polarity via DARE-bench |
| dare-thedevastator-hunt-prices-for-north-american-mammals-class | Hunt Prices for North American Mammals | CC0-1.0 | Kaggle thedevastator/hunt-prices-for-north-american-mammals via DARE-bench |
| uci-wine-quality | Wine Quality | CC-BY-4.0 | archive.ics.uci.edu |
| uci-adult | Adult (census income) | CC-BY-4.0 | archive.ics.uci.edu |
| cellxgene-4d4c7412 | Mouse Craniofacial Expression Cranial Neural Crest | CC-BY-4.0 | cellxgene.cziscience.com |
| cellxgene-6dfbbfae | E9.0: Puck_220718_11 | CC-BY-4.0 | cellxgene.cziscience.com |
The DARE-bench folders come from the train split of Snowflake/dare-bench (commit
7f202a10); each one is a Kaggle dataset, and the license is the one its Kaggle page gave
on 2026-10-26.
Documentation sources and licenses
Only pages whose publisher allows redistribution are included; 81 pages from
other hosts (for example gsea-msigdb.org, otexts.com and mixtape.scunning.com) were left
out. Pages were converted from HTML to text, which is a change to the original. Each
page's source URL is in docs/PACKET.json.
| license | pages | sources (pages) |
|---|---|---|
| BSD-3-Clause | 11,184 | pandas.pydata.org (6,357), numpy.org (1,000), networkx.org (1,000), docs.scipy.org (1,000), scikit-learn.org (969), scanpy.readthedocs.io (309), www.statsmodels.org (238), squidpy.readthedocs.io (139), anndata.readthedocs.io (125), umap-learn.readthedocs.io (30), gseapy.readthedocs.io (8), github.com/broadinstitute/tensorqtl (7), docs.h5py.org (2) |
| PSF-2.0 | 2,120 | docs.python.org (2,120) |
| Apache-2.0 | 1,366 | arrow.apache.org (1,000), www.ensembl.org (132), xgboost.readthedocs.io (109), github.com/theislab/single-cell-best-practices (55), github.com/openvax/pyensembl (27), openvax.github.io (22), causalml.readthedocs.io (21) |
| MIT | 957 | www.pywhy.org (397), pgmpy.org (291), lingam.readthedocs.io (65), bedtools.readthedocs.io (43), daler.github.io (35), causal-learn.readthedocs.io (31), pyranges.readthedocs.io (28), github.com/py-why/EconML (25), zarr.readthedocs.io (23), lightgbm.readthedocs.io (14), github.com/swolock/scrublet (3), github.com/chanzuckerberg/single-cell-curation (2) |
| NCSA | 909 | bashtage.github.io (909) |
| us-government-work | 883 | www.itl.nist.gov (883) |
| BSD-2-Clause | 33 | github.com/intro-stat-learning/ISLP_labs (18), patsy.readthedocs.io (15) |
| GPL-3.0 | 13 | leidenalg.readthedocs.io (7), github.com/slowkow/harmonypy (6) |
Images
The images are built from the tasks' own Dockerfiles: a Python base and the Python and system packages those files install, each under its own license.
The corpus is shared for research on post-training agents. To have something removed, open a discussion on this dataset.
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