ProEmbedEva
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This is for NeuroIPS 2026 paper • 2 items • Updated • 1
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Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 82, in _split_generators
raise ValueError(
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
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 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/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.
This dataset provides the predicted three-dimensional structures corresponding to the Tasks Assessing Protein Embeddings (TAPE) benchmark. Specifically, it encompasses the structural data generated for the stability, fluorescence, and protein-protein interaction (PPI) affinity tasks.
The reference for the TAPE benchmark is:
@inproceedings{tape2019,
author = {Rao, Roshan and Bhattacharya, Nicholas and Thomas, Neil and Duan, Yan and Chen, Xi and Canny, John and Abbeel, Pieter and Song, Yun S},
title = {Evaluating Protein Transfer Learning with TAPE},
booktitle = {Advances in Neural Information Processing Systems}
year = {2019}
}
@article{sarkisyan2016,
title={Local fitness landscape of the green fluorescent protein},
author={Sarkisyan, Karen S and Bolotin, Dmitry A and Meer, Margarita V and Usmanova, Dinara R and Mishin, Alexander S and Sharonov, George V and Ivankov, Dmitry N and Bozhanova, Nina G and Baranov, Mikhail S and Soylemez, Onuralp and others},
journal={Nature},
volume={533},
number={7603},
pages={397},
year={2016},
publisher={Nature Publishing Group}
}
@article{proteinnet,
title={ProteinNet: a standardized data set for machine learning of protein structure},
author={AlQuraishi, Mohammed},
journal={arXiv preprint arXiv:1902.00249},
year={2019}
}
@article{rocklin2017,
title={Global analysis of protein folding using massively parallel design, synthesis, and testing},
author={Rocklin, Gabriel J and Chidyausiku, Tamuka M and Goreshnik, Inna and Ford, Alex and Houliston, Scott and Lemak, Alexander and Carter, Lauren and Ravichandran, Rashmi and Mulligan, Vikram K and Chevalier, Aaron and others},
journal={Science},
volume={357},
number={6347},
pages={168--175},
year={2017},
publisher={American Association for the Advancement of Science}
}
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