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
H: int64
W: int64
scale: int64
feat: int64
n_floats: int64
out_h: int64
out_w: int64
weights: struct<conv_1: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>, block_1.c1_r (... 1801 chars omitted)
child 0, conv_1: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 1, block_1.c1_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 2, block_1.c2_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 3, block_1.c3_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 4, block_2.c1_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 5, block_2.c2_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
...
c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 18, block_6.c3_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 19, conv_2: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 20, conv_cat: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 21, upsampler: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
graph: string
layers: list<item: struct<in_c: int64, out_c: int64, w_off: int64, b_off: int64, prelu_off: int64>>
child 0, item: struct<in_c: int64, out_c: int64, w_off: int64, b_off: int64, prelu_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, w_off: int64
child 3, b_off: int64
child 4, prelu_off: int64
upscale: int64
n_passes: int64
to
{'layers': List({'in_c': Value('int64'), 'out_c': Value('int64'), 'w_off': Value('int64'), 'b_off': Value('int64'), 'prelu_off': Value('int64')}), 'upscale': Value('int64'), 'H': Value('int64'), 'W': Value('int64'), 'n_passes': Value('int64'), 'n_floats': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 478, 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 343, 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 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
H: int64
W: int64
scale: int64
feat: int64
n_floats: int64
out_h: int64
out_w: int64
weights: struct<conv_1: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>, block_1.c1_r (... 1801 chars omitted)
child 0, conv_1: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 1, block_1.c1_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 2, block_1.c2_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 3, block_1.c3_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 4, block_2.c1_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 5, block_2.c2_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
...
c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 18, block_6.c3_r: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 19, conv_2: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 20, conv_cat: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
child 21, upsampler: struct<in_c: int64, out_c: int64, k: int64, w_off: int64, b_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, k: int64
child 3, w_off: int64
child 4, b_off: int64
graph: string
layers: list<item: struct<in_c: int64, out_c: int64, w_off: int64, b_off: int64, prelu_off: int64>>
child 0, item: struct<in_c: int64, out_c: int64, w_off: int64, b_off: int64, prelu_off: int64>
child 0, in_c: int64
child 1, out_c: int64
child 2, w_off: int64
child 3, b_off: int64
child 4, prelu_off: int64
upscale: int64
n_passes: int64
to
{'layers': List({'in_c': Value('int64'), 'out_c': Value('int64'), 'w_off': Value('int64'), 'b_off': Value('int64'), 'prelu_off': Value('int64')}), 'upscale': Value('int64'), 'H': Value('int64'), 'W': Value('int64'), 'n_passes': Value('int64'), 'n_floats': Value('int64')}
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.
playhd — web demo runtime assets
Runtime assets for the playhd in-browser SD→HD upscaler
(github.com/lifeart/playhd). The live demo
(GitHub Pages) fetches these from here. Non-commercial — the bundle includes a
CC-BY-NC-SA model, so the repo as a whole is tagged cc-by-nc-sa-4.0.
Files & licenses (each retains its own license)
| file | what | license | author / source |
|---|---|---|---|
span_data/weights.bin, span_data/spec.json |
SPAN 2xLiveActionV1 weights (reparam'd to WGSL layout) |
CC-BY-NC-SA-4.0 | jcj83429 · https://openmodeldb.info/models/2x-LiveActionV1-SPAN |
compact_data/weights.bin, compact_data/layers.json |
realesr-general-x4v3 weights (reparam'd) |
BSD-3-Clause | Real-ESRGAN, Xintao Wang et al. · https://github.com/xinntao/Real-ESRGAN |
mv_decode.wasm |
minimal FFmpeg→WASM H.264 decoder + motion-vector export | LGPL-2.1+ | FFmpeg · https://ffmpeg.org (build recipe: web_spike/wasm_mv/build_ffmpeg_wasm.sh in the playhd repo) |
clips/BigBuckBunny_640x360_10s_CC-BY.mp4 |
demo clip (10 s) | CC-BY 3.0 | © Blender Foundation · https://peach.blender.org |
The reparameterized SPAN weights are a derivative of a CC-BY-NC-SA-4.0 work and are redistributed here under the same license, with attribution to jcj83429, for non-commercial use. The playhd application code is MIT; these third-party assets are not.
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