NeurEv0/AOMM
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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ValueError
Message: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/NeurEv0/AMP_six_tasks@5dbd584fecf24772aa7c377ecc51d84fccd645c8/AMPOS.json.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
for key, example in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 186, in _generate_tables
raise ValueError(
ValueError: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/NeurEv0/AMP_six_tasks@5dbd584fecf24772aa7c377ecc51d84fccd645c8/AMPOS.json.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.
Dataset
Overview
- AMP-Oriented Six tasks（AMPOS） is the data to train AMP4multitask.
- The dataset is originated from SPADE and open source at Hugging Face.
The ownership of the SPADE Database and AMP_six_tasks dataset belongs to the iGEM team XJTLU_software 2025. If you have any questinons or suggestions, please contact us at igem@xjtlu.edu.cn(Please indicate your organization and purpose of the email).
- The length of the peptides in the dataset is between 5 and 100.
Dataset Structure(AMPOS.json)
"Sequence": {
task_name: label
}
e.g.
"GSKKPVPIIYCNRRTGKCQRM": {
"amp_classification": 1.0,
"bioactivity_classification": [
"Antimicrobial",
"Antibacterial",
"Anti-Gram+",
"Anti-Gram-",
"Antifungal"
],
"half_life_regression": 1800.0,
"mic_regression": {
"Bacillus megaterium": 2.175,
"Bacillus subtilis": 12.000000000000002,
"Botrytis cinerea": 2.5,
"Escherichia coli": 6.940346488174673,
"Fusarium oxysporum": 5.000000000000001,
"Klebsiella pneumoniae": 0.4105197321746724,
"Micrococcus luteus": 2.25,
"Pseudomonas aeruginosa": 10.117063293734716,
"Salmonella typhimurium": 0.4105197321746724,
"Shigella flexneri": 0.1026299330436681,
"Staphylococcus aureus": 105.09305149071614,
"Staphylococcus epidermidis": 6.568315717794759
}
},
"CLLKKLLKK": {
"amp_classification": 1.0,
"bioactivity_classification": [
"Anti-Gram+",
"Anti-Mammalian Cell"
],
"mic_regression": {
"Mycobacterium tuberculosis": 460.20268430703305
}
},
News
- 2025.10: The peptide length of the database is limited to 5 to 100, and the MIC and hemolytic activity data of antimicrobial peptides are updated. Update the preprocess method in
merged_dataloader.py. - 2025.08: AMPOS was born.
Usage
Please see merged_dataloader.py
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