Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
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 80, 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.
AUV-BENCH Data
AUV-BENCH is a public benchmark dataset for evaluating multimodal models on four UI-aesthetics capabilities over executable webpages: scoring, diagnosis, repair, and text-to-UI generation.
Tasks
| Directory | Task | Contents | Scale |
|---|---|---|---|
task1/ |
Aesthetic Scoring | Webpage screenshots + human 8-dimension aesthetic MOS ratings (human_gt_cleaned_mos.csv) |
1,395 samples |
task2/ |
Aesthetic Diagnosis | Paired clean/degraded screenshots + injected-defect ground truth | 695 pairs (660 formal) |
task3/ |
Aesthetic Repair | Degraded webpage HTML + defect specs + 25 pinned render fonts | 660 samples |
task4/ |
Text-to-UI Generation | Generation queries + Top-K visual assets (image + caption) | 1,395 queries |
Directory structure
All data ships as a single archive, auv_bench_data_v1.tar.gz, which extracts
to the following layout:
auv_bench_data_v1/
├── MANIFEST.txt # per-task file/sample counts
├── task1/ manifest.jsonl images/ human_gt_cleaned_mos.csv
├── task2/ manifest.jsonl images/
├── task3/ cohort.json defect_specs.jsonl pages/ render_fonts/fonts/
└── task4/ queries.jsonl cohort.json freeze.json inputs/
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