Datasets:

Emulated-Inc
/

rnafold

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 4 new columns ({'sequence', 'target_id', 'temporal_cutoff', 'all_sequences'}) and 6 missing columns ({'x_1', 'ID', 'resid', 'y_1', 'z_1', 'resname'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Emulated-Inc/rnafold/data/train_sequences.csv (at revision 7dba8fe06c9cf9dfa5436c60a91059fef1687465), ['hf://datasets/Emulated-Inc/rnafold@7dba8fe06c9cf9dfa5436c60a91059fef1687465/data/train_labels.csv', 'hf://datasets/Emulated-Inc/rnafold@7dba8fe06c9cf9dfa5436c60a91059fef1687465/data/train_sequences.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              target_id: string
              sequence: string
              temporal_cutoff: string
              all_sequences: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 771
              to
              {'ID': Value('string'), 'resname': Value('string'), 'resid': Value('int64'), 'x_1': Value('float64'), 'y_1': Value('float64'), 'z_1': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 4 new columns ({'sequence', 'target_id', 'temporal_cutoff', 'all_sequences'}) and 6 missing columns ({'x_1', 'ID', 'resid', 'y_1', 'z_1', 'resname'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Emulated-Inc/rnafold/data/train_sequences.csv (at revision 7dba8fe06c9cf9dfa5436c60a91059fef1687465), ['hf://datasets/Emulated-Inc/rnafold@7dba8fe06c9cf9dfa5436c60a91059fef1687465/data/train_labels.csv', 'hf://datasets/Emulated-Inc/rnafold@7dba8fe06c9cf9dfa5436c60a91059fef1687465/data/train_sequences.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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.

ID string	resname string	resid int64	x_1 float64	y_1 float64	z_1 float64
e00001_2_1	G	1	282.066	359.32	170.66
e00001_2_2	U	2	286.113	355.572	172.299
e00001_2_3	C	3	287.301	351.222	175.304
e00001_2_4	U	4	285.863	348.514	179.575
e00001_2_5	C	5	282.739	345.92	182.783
e00001_2_6	C	6	277.729	344.672	185.355
e00001_2_7	G	7	272.206	343.529	184.657
e00001_2_8	U	8	270.179	336.565	189.097
e00001_2_9	A	9	263.415	335.531	194.539
e00001_2_10	G	10	261.15	341.778	197.734
e00001_2_11	U	11	266.711	343.587	199.059
e00001_2_12	G	12	272.033	342.858	198.799
e00001_2_13	U	13	274.902	339.041	196.478
e00001_2_14	A	14	277.266	333.554	195.28
e00001_2_15	G	15	277.386	330.361	190.725
e00001_2_16	C	16	284.304	325.523	187.096
e00001_2_17	G	17	278.604	324.373	180.492
e00001_2_18	G	18	274.658	319.065	182.869
e00001_2_19	U	19	272.312	322.518	189.977
e00001_2_20	U	20	265.825	321.352	193.171
e00001_2_21	A	21	270.209	328.186	190.979
e00001_2_22	U	22	273.671	329.125	197.028
e00001_2_23	C	23	274.09	332.597	201.558
e00001_2_24	A	24	272.168	336.483	204.607
e00001_2_25	C	25	268.085	339.71	205.395
e00001_2_26	G	26	262.984	340.499	204.38
e00001_2_27	U	27	257.95	337.903	203.861
e00001_2_28	U	28	254.009	334.317	205.478
e00001_2_29	C	29	252.542	330.203	209.089
e00001_2_30	G	30	253.244	327.743	213.819
e00001_2_31	C	31	255.269	327.802	218.754
e00001_2_32	C	32	257.815	330.697	223.1
e00001_2_33	U	33	255.385	335.185	225.806
e00001_2_34	A	34	249.861	338.494	229.533
e00001_2_35	A	35	251.509	340.795	224.968
e00001_2_36	C	36	255.546	342.49	221.513
e00001_2_37	A	37	260.826	341.931	220.686
e00001_2_38	C	38	264.65	338.336	220.899
e00001_2_39	G	39	264.567	333.051	220.218
e00001_2_40	C	40	262.97	328.004	218.127
e00001_2_41	G	41	260.508	325.044	214.174
e00001_2_42	A	42	258.38	325.26	209.186
e00001_2_43	A	43	257.053	327.257	204.433
e00001_2_44	A	44	256.458	330.374	200.038
e00001_2_45	G	45	259.118	333.228	196.488
e00001_2_46	G	46	263.43	333.784	190.816
e00001_2_47	U	47	260.73	336.28	183.029
e00001_2_48	C	48	268.577	334.319	185.888
e00001_2_49	C	49	267.806	342.56	181.823
e00001_2_50	U	50	266.237	341.548	176.019
e00001_2_51	C	51	266.526	338.914	171.413
e00001_2_52	G	52	269.399	335.591	168.036
e00001_2_53	G	53	273.297	331.973	167.648
e00001_2_54	U	54	276.862	327.808	168.883
e00001_2_55	U	55	276.194	323.194	171.629
e00001_2_56	C	56	273.141	316.671	172.526
e00001_2_57	G	57	272.532	320.666	176.524
e00001_2_58	A	58	273.747	327.9	177.83
e00001_2_59	A	59	271.868	331.39	183.83
e00001_2_60	A	60	277.252	331.481	182.061
e00001_2_61	C	61	280.461	330.799	175.596
e00001_2_62	C	62	279.594	334.088	171.266
e00001_2_63	G	63	276.849	338.369	168.413
e00001_2_64	G	64	273.646	342.46	168.494
e00001_2_65	G	65	269.296	345.302	171.652
e00001_2_66	C	66	267.632	348.319	176.161
e00001_2_67	G	67	269.682	350.07	180.934
e00001_2_68	G	68	273.905	351.343	184.56
e00001_2_69	A	69	278.939	352.925	185.93
e00001_2_70	A	70	284.392	354.253	185.665
e00001_2_71	A	71	288.647	355.997	182.73
e00001_2_72	C	72	290.195	359.24	178.238
e00001_2_73	A	73	289.04	364.249	175.772
e00001_2_74	C	74	296.126	366.019	175.404
e00001_2_75	C	75	300	370.262	172.058
e00001_2_76	A	76	299.237	374.826	170.521
e00001_3_1	G	1	315.488	324.843	180.858
e00001_3_2	C	2	316.975	322.994	186.28
e00001_3_3	C	3	316.027	321.577	191.392
e00001_3_4	C	4	312.423	320.976	195.217
e00001_3_5	G	5	307.55	320.924	197.537
e00001_3_6	G	6	301.467	319.219	197.087
e00001_3_7	A	7	297.517	316.7	194.539
e00001_3_8	U	8	294.21	311.968	199.787
e00001_3_9	A	9	286.397	311.755	202.332
e00001_3_10	G	10	282.877	318.487	201.9
e00001_3_11	C	11	287.779	320.996	203.978
e00001_3_12	U	12	292.675	321.117	206.275
e00001_3_13	C	13	296.453	317.642	206.73
e00001_3_14	A	14	299.026	312.239	208.997
e00001_3_15	G	15	300.771	307.748	206.436
e00001_3_16	C	16	308.296	302.627	207.484
e00001_3_17	U	17	305.927	298.061	200.421
e00001_3_18	G	18	301.681	293.547	203.607
e00001_3_19	U	19	289.442	298.234	207.694
e00001_3_20	A	20	294.535	304.417	204.674
e00001_3_21	G	21	295.112	308.155	210.571
e00001_3_22	A	22	293.774	313.115	213.086
e00001_3_23	G	23	290.235	317.222	213.79
e00001_3_24	C	24	286.394	319.906	211.69

End of preview.

RNA 3D Structure Library and Targets

Predict the 3D structure of an RNA molecule from its sequence, as C1' atom coordinates per residue, given a library of thousands of experimentally solved RNA structures. train_sequences.csv and train_labels.csv give every training target's sequence and C1' coordinates, structures/ holds one coordinate-only mmCIF per training assembly, and test_sequences.csv lists the held-out targets, which were solved after every training structure was published.

The data tree lives under data/, exactly as the benchmark environment presents it at /app/rnafold. Its own description is at data/README.md.

5475 files, 20866488799 bytes (19.4 GiB)
structure hash (sha256 over sorted path\tsize lines): 3eeb4e11c330c69dda27be1841c1a5a01eee90bf61d1543428635c44f0bc173f
data.manifest.tsv at the repo root lists every file as sha256 size path

Use

from huggingface_hub import snapshot_download

snapshot_download("Emulated-Inc/rnafold", repo_type="dataset", revision="REVISION",
                  local_dir="./rnafold", allow_patterns="data/*")

Pin revision to a commit sha rather than a branch if you need reproducibility.

Provenance and licence

Every byte of this dataset is derived from the RCSB Protein Data Bank (https://www.rcsb.org), whose archive is free of all copyright restrictions and fully and freely available for both non-commercial and commercial use (CC0). Please cite Berman et al. (2000) Nucleic Acids Research 28:235-242 and Burley et al. (2023) Nucleic Acids Research 51:D488-D508. Structures are re-emitted coordinate-only with opaque identifiers and a rigid transform per structure; the task design follows the Stanford RNA 3D Folding Kaggle competition as a template only, and no competition-distributed data is included.

Downloads last month: -

Total file size:

20.9 GB

RNA 3D Structure Library and Targets

Contents

Use

Provenance and licence