Error code: ConfigNamesError Exception: FileNotFoundError Message: Couldn't find a dataset script at /src/services/worker/Birchlabs/sdxl-latents-artbench/sdxl-latents-artbench.py or any data file in the same directory. Couldn't find 'Birchlabs/sdxl-latents-artbench' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in Birchlabs/sdxl-latents-artbench. Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 65, in compute_config_names_response for config in sorted(get_dataset_config_names(path=dataset, token=hf_token)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names dataset_module = dataset_module_factory( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1507, in dataset_module_factory raise FileNotFoundError( FileNotFoundError: Couldn't find a dataset script at /src/services/worker/Birchlabs/sdxl-latents-artbench/sdxl-latents-artbench.py or any data file in the same directory. Couldn't find 'Birchlabs/sdxl-latents-artbench' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in Birchlabs/sdxl-latents-artbench.

https://github.com/liaopeiyuan/artbench samples encoded to float16 SDXL latents via Ollin VAE.

Dataset created using this script.

Didn't bother saving mean & logvar, because variance is low enough it's not worth the doubling of filesize to retain.
Sampled from diagonal gaussian distribution, saved the resulting latents.
Also kept the original image.

Schema/usage:

from typing import TypedDict, Iterator
from webdataset import WebDataset
Sample = TypedDict('Sample', {
  '__key__': str,
  '__url__': str,
  'cls.txt': bytes, # UTF-8 encoded class id from 0 to 9 inclusive
  'img.png': bytes, # PIL image, serialized. 256*256px
  'latent.pth': bytes, # FloatTensor, serialized. 32*32 latents
})

it: Iterator[Sample] = WebDataset('train/{00000..00004}.tar')

for sample in it:
  pass

The data sources of ArtBench-10 is released under a Fair Use license, as requested by WikiArt, Ukiyo-e.org database and The Surrealism Website.
For more information, see https://www.wikiart.org/en/terms-of-use, https://ukiyo-e.org/about and https://surrealism.website/

train: 50000 samples
test: 10000 samples

# test/avg/val.pt (mean):
[-0.11362826824188232, -0.7059057950973511, 0.4819808006286621, 2.2327630519866943]
# test/avg/sq.pt:
[52.59075927734375, 30.115631103515625, 44.977020263671875, 30.228885650634766]
# std
# (sq - val**2)**.5
[7.251058578491211, 5.442180633544922, 6.689148902893066, 5.024306297302246]
# 1/std
[0.1379109025001526, 0.18374986946582794, 0.14949584007263184, 0.19903245568275452]

# train/avg/val.pt (mean):
[-0.1536690890789032, -0.7142514586448669, 0.4706766605377197, 2.24863600730896]
# train/avg/sq.pt:
[51.99677276611328, 30.184646606445312, 44.909732818603516, 30.234216690063477]
# std
# (sq - val**2)**.5
[7.2092413902282715, 5.447429656982422, 6.68492317199707, 5.017753601074219]
# 1/std
[0.1387108564376831, 0.18357281386852264, 0.14959034323692322, 0.1992923617362976]