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
model_condition: string
prompt_id: string
subset: string
prompt_sha256: string
seed: int64
recipe: struct<backend: string, repo: string, source: null, height: int64, width: int64, frames: int64, fps: (... 502 chars omitted)
child 0, backend: string
child 1, repo: string
child 2, source: null
child 3, height: int64
child 4, width: int64
child 5, frames: int64
child 6, fps: int64
child 7, output_frames: int64
child 8, steps: list<item: int64>
child 0, item: int64
child 9, guidance: int64
child 10, precision: string
child 11, seed: int64
child 12, negative_prompt: string
child 13, input_interface: string
child 14, track: string
child 15, duration_target_s: int64
child 16, duration_requested_s: double
child 17, duration_supported_max_s: null
child 18, duration_limit_source: null
child 19, attention_backend: string
child 20, offload: bool
child 21, resources: list<item: struct<repo: string, revision: string, files: list<item: string>, check_indices: list<ite (... 12 chars omitted)
child 0, item: struct<repo: string, revision: string, files: list<item: string>, check_indices: list<item: string>>
child 0, repo: string
child 1, revision: string
child 2, files: list<item: string>
child 0, item: string
child 3, check_indices: list<item: string>
child 0, item: string
child 22, source_files: list<item: null>
child 0, item: null
child 23, sampler: string
co
...
g
child 5, flash-attn: null
generator_kwargs: struct<prompt: string, negative_prompt: string, height: int64, width: int64, num_frames: int64, guid (... 101 chars omitted)
child 0, prompt: string
child 1, negative_prompt: string
child 2, height: int64
child 3, width: int64
child 4, num_frames: int64
child 5, guidance_scale: int64
child 6, pyramid_num_inference_steps_list: list<item: int64>
child 0, item: int64
child 7, is_amplify_first_chunk: bool
frame_count: int64
fps: double
resolution: string
duration_written_s: double
hardware: string
cuda_version: string
gpu_memory_total_bytes: int64
peak_allocated_bytes: int64
peak_reserved_bytes: int64
run_signature: string
prompt_text: string
track: string
input_interface: string
checkpoint: string
repo_commit: null
precision: string
gpu_count: int64
steps: list<item: int64>
child 0, item: int64
guidance: int64
duration_target_s: int64
duration_requested_s: double
duration_supported_max_s: null
duration_limit_source: null
wall_time_s: double
model_load_time_s: double
video_bytes: int64
video_sha256: string
mps_enabled: bool
renamed_from: struct<model_condition: string, runner_files: struct<scripts/video_runtime.py: string, scripts/backe (... 33 chars omitted)
child 0, model_condition: string
child 1, runner_files: struct<scripts/video_runtime.py: string, scripts/backends/diffusers_models.py: string>
child 0, scripts/video_runtime.py: string
child 1, scripts/backends/diffusers_models.py: string
to
{'model_condition': Value('string'), 'prompt_id': Value('string'), 'subset': Value('string'), 'prompt_sha256': Value('string'), 'seed': Value('int64'), 'recipe': {'backend': Value('string'), 'repo': Value('string'), 'source': Value('null'), 'height': Value('int64'), 'width': Value('int64'), 'frames': Value('int64'), 'fps': Value('int64'), 'output_frames': Value('int64'), 'steps': List(Value('int64')), 'guidance': Value('int64'), 'precision': Value('string'), 'seed': Value('int64'), 'negative_prompt': Value('string'), 'input_interface': Value('string'), 'track': Value('string'), 'duration_target_s': Value('int64'), 'duration_requested_s': Value('float64'), 'duration_supported_max_s': Value('null'), 'duration_limit_source': Value('null'), 'attention_backend': Value('string'), 'offload': Value('bool'), 'resources': List({'repo': Value('string'), 'revision': Value('string'), 'files': List(Value('string')), 'check_indices': List(Value('string'))}), 'source_files': List(Value('null')), 'sampler': Value('string')}, 'conditioning': {'artifact_sha256': {}}, 'artifacts': {'checkpoints': {'BestWishYsh/Helios-Distilled': {'path': Value('string'), 'revision': Value('string')}}, 'repo_commit': Value('null'), 'source_diff_sha256': Value('null'), 'source': Value('null')}, 'runner_files': {'scripts/run_model.py': Value('string'), 'scripts/video_runtime.py': Value('string'), 'scripts/model_registry.py': Value('string'), 'scripts/backends/__init__.py': Value('string'), 'scripts/backends/cli_mod
...
s.py': Value('string'), 'scripts/backends/sana_model.py': Value('string')}, 'versions': {'torch': Value('string'), 'diffusers': Value('string'), 'transformers': Value('string'), 'numpy': Value('string'), 'av': Value('string'), 'flash-attn': Value('null')}, 'generator_kwargs': {'prompt': Value('string'), 'negative_prompt': Value('string'), 'height': Value('int64'), 'width': Value('int64'), 'num_frames': Value('int64'), 'guidance_scale': Value('int64'), 'pyramid_num_inference_steps_list': List(Value('int64')), 'is_amplify_first_chunk': Value('bool')}, 'frame_count': Value('int64'), 'fps': Value('float64'), 'resolution': Value('string'), 'duration_written_s': Value('float64'), 'hardware': Value('string'), 'cuda_version': Value('string'), 'gpu_memory_total_bytes': Value('int64'), 'peak_allocated_bytes': Value('int64'), 'peak_reserved_bytes': Value('int64'), 'run_signature': Value('string'), 'prompt_text': Value('string'), 'track': Value('string'), 'input_interface': Value('string'), 'checkpoint': Value('string'), 'repo_commit': Value('null'), 'precision': Value('string'), 'gpu_count': Value('int64'), 'steps': List(Value('int64')), 'guidance': Value('int64'), 'duration_target_s': Value('int64'), 'duration_requested_s': Value('float64'), 'duration_supported_max_s': Value('null'), 'duration_limit_source': Value('null'), 'wall_time_s': Value('float64'), 'model_load_time_s': Value('float64'), 'video_bytes': Value('int64'), 'video_sha256': Value('string'), 'mps_enabled': Value('bool')}
because column names don't match
Traceback: 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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
model_condition: string
prompt_id: string
subset: string
prompt_sha256: string
seed: int64
recipe: struct<backend: string, repo: string, source: null, height: int64, width: int64, frames: int64, fps: (... 502 chars omitted)
child 0, backend: string
child 1, repo: string
child 2, source: null
child 3, height: int64
child 4, width: int64
child 5, frames: int64
child 6, fps: int64
child 7, output_frames: int64
child 8, steps: list<item: int64>
child 0, item: int64
child 9, guidance: int64
child 10, precision: string
child 11, seed: int64
child 12, negative_prompt: string
child 13, input_interface: string
child 14, track: string
child 15, duration_target_s: int64
child 16, duration_requested_s: double
child 17, duration_supported_max_s: null
child 18, duration_limit_source: null
child 19, attention_backend: string
child 20, offload: bool
child 21, resources: list<item: struct<repo: string, revision: string, files: list<item: string>, check_indices: list<ite (... 12 chars omitted)
child 0, item: struct<repo: string, revision: string, files: list<item: string>, check_indices: list<item: string>>
child 0, repo: string
child 1, revision: string
child 2, files: list<item: string>
child 0, item: string
child 3, check_indices: list<item: string>
child 0, item: string
child 22, source_files: list<item: null>
child 0, item: null
child 23, sampler: string
co
...
g
child 5, flash-attn: null
generator_kwargs: struct<prompt: string, negative_prompt: string, height: int64, width: int64, num_frames: int64, guid (... 101 chars omitted)
child 0, prompt: string
child 1, negative_prompt: string
child 2, height: int64
child 3, width: int64
child 4, num_frames: int64
child 5, guidance_scale: int64
child 6, pyramid_num_inference_steps_list: list<item: int64>
child 0, item: int64
child 7, is_amplify_first_chunk: bool
frame_count: int64
fps: double
resolution: string
duration_written_s: double
hardware: string
cuda_version: string
gpu_memory_total_bytes: int64
peak_allocated_bytes: int64
peak_reserved_bytes: int64
run_signature: string
prompt_text: string
track: string
input_interface: string
checkpoint: string
repo_commit: null
precision: string
gpu_count: int64
steps: list<item: int64>
child 0, item: int64
guidance: int64
duration_target_s: int64
duration_requested_s: double
duration_supported_max_s: null
duration_limit_source: null
wall_time_s: double
model_load_time_s: double
video_bytes: int64
video_sha256: string
mps_enabled: bool
renamed_from: struct<model_condition: string, runner_files: struct<scripts/video_runtime.py: string, scripts/backe (... 33 chars omitted)
child 0, model_condition: string
child 1, runner_files: struct<scripts/video_runtime.py: string, scripts/backends/diffusers_models.py: string>
child 0, scripts/video_runtime.py: string
child 1, scripts/backends/diffusers_models.py: string
to
{'model_condition': Value('string'), 'prompt_id': Value('string'), 'subset': Value('string'), 'prompt_sha256': Value('string'), 'seed': Value('int64'), 'recipe': {'backend': Value('string'), 'repo': Value('string'), 'source': Value('null'), 'height': Value('int64'), 'width': Value('int64'), 'frames': Value('int64'), 'fps': Value('int64'), 'output_frames': Value('int64'), 'steps': List(Value('int64')), 'guidance': Value('int64'), 'precision': Value('string'), 'seed': Value('int64'), 'negative_prompt': Value('string'), 'input_interface': Value('string'), 'track': Value('string'), 'duration_target_s': Value('int64'), 'duration_requested_s': Value('float64'), 'duration_supported_max_s': Value('null'), 'duration_limit_source': Value('null'), 'attention_backend': Value('string'), 'offload': Value('bool'), 'resources': List({'repo': Value('string'), 'revision': Value('string'), 'files': List(Value('string')), 'check_indices': List(Value('string'))}), 'source_files': List(Value('null')), 'sampler': Value('string')}, 'conditioning': {'artifact_sha256': {}}, 'artifacts': {'checkpoints': {'BestWishYsh/Helios-Distilled': {'path': Value('string'), 'revision': Value('string')}}, 'repo_commit': Value('null'), 'source_diff_sha256': Value('null'), 'source': Value('null')}, 'runner_files': {'scripts/run_model.py': Value('string'), 'scripts/video_runtime.py': Value('string'), 'scripts/model_registry.py': Value('string'), 'scripts/backends/__init__.py': Value('string'), 'scripts/backends/cli_mod
...
s.py': Value('string'), 'scripts/backends/sana_model.py': Value('string')}, 'versions': {'torch': Value('string'), 'diffusers': Value('string'), 'transformers': Value('string'), 'numpy': Value('string'), 'av': Value('string'), 'flash-attn': Value('null')}, 'generator_kwargs': {'prompt': Value('string'), 'negative_prompt': Value('string'), 'height': Value('int64'), 'width': Value('int64'), 'num_frames': Value('int64'), 'guidance_scale': Value('int64'), 'pyramid_num_inference_steps_list': List(Value('int64')), 'is_amplify_first_chunk': Value('bool')}, 'frame_count': Value('int64'), 'fps': Value('float64'), 'resolution': Value('string'), 'duration_written_s': Value('float64'), 'hardware': Value('string'), 'cuda_version': Value('string'), 'gpu_memory_total_bytes': Value('int64'), 'peak_allocated_bytes': Value('int64'), 'peak_reserved_bytes': Value('int64'), 'run_signature': Value('string'), 'prompt_text': Value('string'), 'track': Value('string'), 'input_interface': Value('string'), 'checkpoint': Value('string'), 'repo_commit': Value('null'), 'precision': Value('string'), 'gpu_count': Value('int64'), 'steps': List(Value('int64')), 'guidance': Value('int64'), 'duration_target_s': Value('int64'), 'duration_requested_s': Value('float64'), 'duration_supported_max_s': Value('null'), 'duration_limit_source': Value('null'), 'wall_time_s': Value('float64'), 'model_load_time_s': Value('float64'), 'video_bytes': Value('int64'), 'video_sha256': Value('string'), 'mps_enabled': Value('bool')}
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.
TRVG-output
60-second videos generated for the TRVG pilot-50 release: 21 subsets × 50 prompts = 1050 prompts per model, seed 42, each model run with its official inference recipe.
Layout: <model>/<subset>/<prompt_id>.mp4 with <model>/<subset>/<prompt_id>.json beside it (prompt text,
seed, full recipe, checkpoint revision, runtime versions, timing and memory).
| Model | Videos | Resolution | FPS | Frames |
|---|---|---|---|---|
| LongLive-2.0-5B | 1050 | 1280×704 | 24 | 1437 (59.875 s) |
| Helios-Distilled | 1050 | 640×384 | 24 | 1440 |
| LTX-2.5-22B-Distilled-Extend | 1050 | 1280×768 | 24 | 1440 |
| LongSANA-Video-2B | 1050 | 832×480 | 16 | 960 |
| LTX-2.5-22B-Extend | 1050 | 1280×768 | 24 | 1440 |
LTX-2.5-22B-Extend (dev two-stage recipe) and LTX-2.5-22B-Distilled-Extend (distilled recipe) generate by chunked continuation (97-frame windows, 25-frame carry); they belong to the conditioned-extension track and are reported separately from the direct text-to-video models.
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