The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 80, in _split_generators
raise ValueError(
...<2 lines>...
)
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 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/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.
ProtEnv: predicted structures for four ProtCompass downstream tasks
ESMFold structures for the four downstream tasks of ProtCompass whose source datasets provide no structure: stability, fluorescence, solubility and PPI affinity. The structure encoders read these files on these four tasks.
- Code, result tables and analysis scripts: https://anonymous.4open.science/r/ProEmbedEva-C4F6
- Embeddings, labels, task manifests and input audit: https://huggingface.co/Anonymoususer2223/ProtCompass_Embeddings
Contents
| File | Task | PDB files | Size (GB) | Extracts to |
|---|---|---|---|---|
predicted_structures/predictions_train.tar.gz |
stability, training split | 52,029 | 0.36 | predictions_train/ |
predicted_structures/predictions_test.tar.gz |
stability, test split | 12,851 | 0.09 | predictions_test/ |
predicted_structures/fluorescence.tar.gz |
fluorescence | 54,025 | 2.01 | predictions_fluorescence/ |
predicted_structures/solubility.tar.gz |
solubility | 70,201 | 2.70 | predictions_solubility/ |
predicted_structures/ppi_affinity.tar.gz |
PPI affinity, one structure per chain | 2,601 | 0.05 | predictions_ppi_affinity/ |
Each archive holds one folder of PDB files. A file holds one predicted chain as ATOM records, with the per-residue pLDDT (0 to 100) in the B-factor column.
Use with the code
The archives hold every structure that was predicted. The task manifests in the embeddings repository
(extract/manifest/<task>.csv) select the proteins each task uses and give each protein's structure file in the
column structure_path, relative to the directory that holds the code repository's protcompass/ folder. Extract
each archive into the folder its manifest names:
| Task | Folder named in structure_path |
|---|---|
| stability | downstream_tasks/data/tape/tape_structures/stability/predictions_train/ and .../predictions_test/ |
| fluorescence | protcompass/extract/structures/predictions_fluorescence/ |
| solubility | protcompass/extract/structures/predictions_solubility/ |
| PPI affinity | protcompass/extract/structures/predictions_ppi_affinity/ |
from huggingface_hub import hf_hub_download
import tarfile
path = hf_hub_download("Anonymoususer2223/ProtEnv", "predicted_structures/fluorescence.tar.gz", repo_type="dataset")
tarfile.open(path).extractall("protcompass/extract/structures/")
Notes
- The structures are predictions, not experimental structures. The manifests record each protein's mean pLDDT
(
mean_plddt). Its median over the manifest rows is 70.0 for stability, 46.4 for fluorescence, 83.7 for solubility and 92.4 for PPI affinity. - The experimental (PDB), AlphaFold DB, SCOPe and CATH structures of the other tasks are public and are not redistributed here. The code repository has the scripts that fetch them.
Citation
Citation information will be added after the anonymous review period.
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