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/folder_based_builder/folder_based_builder.py", line 251, in _split_generators
raise ValueError(
"`file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files"
)
ValueError: `file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files
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.
VideoSynthesis
AI-generated face-swap clips from the representative-clip strategy. Legacy runs, full source videos, reference portraits, model weights, and credentials are not included. Each published clip is a finalized DreamID-V output upscaled with SeedVR2, with the driving clip's original audio retained.
representative/metadata.jsonl indexes the current version of each sample. Video
paths are repository-relative. Adjacent JSON sidecars preserve the per-version
metadata. Files use content-addressed names; older versions may remain in Git
history or the repository, so use the index rather than globbing all videos.
Metadata identifies source IDs and time windows, not verified real-world names.
The clean windows are selected by automated screening; this is not a guarantee
that every output is artifact-free. Splits marked unassigned are not a
validated identity-disjoint train/test split. Reused identities and source
segments must be accounted for before training or evaluation.
This upload does not grant additional rights to source media or model assets. Source permissions and applicable model licenses remain the uploader's responsibility. Synthetic outputs must not be represented as authentic footage.
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