The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Expected object or value
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
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column(/run/runtime/backendContract/contracts/[]/params/device/options) changed from array to object in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 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 valueNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MoDiff Template Gallery
This public Dataset contains rights-approved media, input fixtures, posters, and provenance records used by the open-source MoDiff template Gallery. MoDiff executes local workflows with Hugging Face Diffusers and Modular Diffusers. The Dataset exists so users can inspect or reuse the public examples without adding large binary files to the application source repository.
Versioning and integrity
MoDiff releases pin this Dataset by its immutable Hub commit SHA. The file
_modiff/template-assets.v1.json records the byte length, media type, and
SHA-256 digest of every application-owned file. A moving branch such as main
is never used by a released application.
Repository structure
template-gallery/manifest.jsonis MoDiff's reviewed-example manifest.template-gallery/runtime-inputs/contains byte-pinned workflow inputs.template-gallery/reviews/contains review and provenance metadata.- Other files under
template-gallery/are generated examples and browser derivatives. _modiff/template-assets.v1.jsonis the deterministic storage manifest._modiff/template-asset-rights.v1.jsonbinds the redistribution review to the exact SHA-256 identity of every published file.
Contents and curation
The Dataset is a small, curated application fixture rather than a general
training corpus. It may contain generated image, audio, and video examples;
browser-friendly posters and previews; workflow input fixtures; and JSON
review records. Every published byte must have an approved record in the
rights ledger for the same path and SHA-256 digest. That record identifies the
creator or rightsholder, creation method, source and model terms, attribution,
likeness and mark review, reviewer, and review date.
Technical generation receipts and quality reviews are supporting evidence, not permission to redistribute a file. Maintainers exclude candidates whose source, consent, model terms, or redistribution rights cannot be established.
Intended use
The files support browsing, reproducing, and reviewing MoDiff workflows. They are not a training corpus and are not intended to identify or represent real people. Maintainers should remove an asset if its provenance or redistribution rights cannot be demonstrated.
The media is not a quality benchmark, safety evaluation, or representative sample of any model's possible outputs. It must not be used to infer model fitness, demographic performance, or the rights status of newly generated media.
Limitations and potential bias
The Gallery is selected by MoDiff maintainers to demonstrate particular workflows, so it reflects those curatorial choices, prompts, checkpoints, hardware, and generation settings. Generated outputs may reproduce biases, artifacts, or limitations of the referenced models. A successful rights review does not certify factual accuracy, suitability, or freedom from all third-party claims. Revisions are immutable snapshots; later removals or corrections do not alter an older pinned release.
Privacy, safety, and takedowns
Do not publish private prompts, local paths, credentials, personal data, unconsented real-person likenesses, or confidential source media. Public provenance records must be reviewed and redacted before upload. Report a privacy, consent, attribution, trademark, or redistribution concern through the MoDiff Client security-reporting process. Maintainers should hold the affected asset immediately and publish a corrected Dataset revision; the application source must then pin that new immutable revision.
Licenses and attribution
The MoDiff application source is licensed separately. Apache-2.0 for the application does not relicense model-generated media, input material, model weights, or third-party marks. Review the per-template provenance records and the licenses or terms of every referenced model before redistributing or using an asset beyond the MoDiff Gallery. Where provenance or redistribution rights are incomplete, the file must not be published in this Dataset. A technical generation receipt is not itself a copyright, consent, trademark, or redistribution grant.
Updates
Maintainers generate and verify the storage manifest locally, upload one reviewed asset set, and pin the resulting commit SHA in MoDiff. Replacing a file creates a new asset-set identity and requires a new pinned Dataset commit. Historical application releases continue resolving their original revision.
Provisional publication
This revision contains only the rights-approved subset and is intentionally incomplete. It must not be activated as MoDiff's runtime Dataset. The complete local asset set remains authoritative until the pending permissions are resolved.
Files withheld from this revision:
template-gallery/ace_step_chinese_new_year_lora.card-poster.pngtemplate-gallery/ace_step_chinese_new_year_lora.wavtemplate-gallery/flux_lora_ghibli_story.card-poster.webptemplate-gallery/flux_lora_ghibli_story.webp
- Downloads last month
- 479