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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: OSError
Message: cannot find loader for this HDF5 file
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2097, in __iter__
example = _apply_feature_types_on_example(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1635, in _apply_feature_types_on_example
decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 2044, in decode_example
return {
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 2045, in <dictcomp>
column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1405, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/image.py", line 188, in decode_example
image.load() # to avoid "Too many open files" errors
File "/src/services/worker/.venv/lib/python3.9/site-packages/PIL/ImageFile.py", line 366, in load
raise OSError(msg)
OSError: cannot find loader for this HDF5 fileNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
This dataset includes WD EVA v2 large embeddings for danbooru images. Pixiv will be added later. Tensors under w are direct outputs and match indexes for WD EVA model. Tensors under e are from WD EVA as well however these strips the classifiaction head, they are smaller and suitable for deduplication computing for example. The indexes of w, e and f (filename) match.
WD EVA Model: https://huggingface.co/SmilingWolf/wd-eva02-large-tagger-v3
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