Dataset Viewer
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: CastError
Message: Couldn't cast
dataset_id: string
row: struct<sequence: string, set: string, target: string, validation: string>
child 0, sequence: string
child 1, set: string
child 2, target: string
child 3, validation: string
row_index: int64
source_file: string
format: string
total_rows: int64
tables: list<item: struct<bytes: int64, category: string, dataset_id: string, output_file: string, rows: int (... 41 chars omitted)
child 0, item: struct<bytes: int64, category: string, dataset_id: string, output_file: string, rows: int64, source_ (... 29 chars omitted)
child 0, bytes: int64
child 1, category: string
child 2, dataset_id: string
child 3, output_file: string
child 4, rows: int64
child 5, source_file: string
child 6, status: string
category: string
to
{'category': Value('string'), 'dataset_id': Value('string'), 'format': Value('string'), 'tables': List({'bytes': Value('int64'), 'category': Value('string'), 'dataset_id': Value('string'), 'output_file': Value('string'), 'rows': Value('int64'), 'source_file': Value('string'), 'status': Value('string')}), 'total_rows': Value('int64')}
because column names don't match
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 272, 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 "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, 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 299, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
dataset_id: string
row: struct<sequence: string, set: string, target: string, validation: string>
child 0, sequence: string
child 1, set: string
child 2, target: string
child 3, validation: string
row_index: int64
source_file: string
format: string
total_rows: int64
tables: list<item: struct<bytes: int64, category: string, dataset_id: string, output_file: string, rows: int (... 41 chars omitted)
child 0, item: struct<bytes: int64, category: string, dataset_id: string, output_file: string, rows: int64, source_ (... 29 chars omitted)
child 0, bytes: int64
child 1, category: string
child 2, dataset_id: string
child 3, output_file: string
child 4, rows: int64
child 5, source_file: string
child 6, status: string
category: string
to
{'category': Value('string'), 'dataset_id': Value('string'), 'format': Value('string'), 'tables': List({'bytes': Value('int64'), 'category': Value('string'), 'dataset_id': Value('string'), 'output_file': Value('string'), 'rows': Value('int64'), 'source_file': Value('string'), 'status': Value('string')}), 'total_rows': Value('int64')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
FLIP v2
FLIP v2 benchmark splits for protein engineering tasks (amylase, hydrolase, etc.), normalized to newline-delimited JSON.
Processed and uploaded by the MegaData post-download pipeline (internal repo). Original source: https://github.com/J-SNACKKB/FLIP.
Statistics
| Table files | 16 |
| Total rows | 890,356 |
| Total bytes | 440.98 MiB (462,398,539) |
Tables
| Table | Rows | Bytes |
|---|---|---|
data_unpacked_labeled_flip2_amylase_by_mutation.csv.jsonl |
3,706 | 2.18 MiB |
data_unpacked_labeled_flip2_amylase_close_to_far.csv.jsonl |
3,706 | 2.18 MiB |
data_unpacked_labeled_flip2_amylase_far_to_close.csv.jsonl |
3,706 | 2.18 MiB |
data_unpacked_labeled_flip2_amylase_one_to_many.csv.jsonl |
3,706 | 2.18 MiB |
data_unpacked_labeled_flip2_hydro_low_to_high.csv.jsonl |
24,935 | 6.02 MiB |
data_unpacked_labeled_flip2_hydro_three_to_many.csv.jsonl |
24,935 | 6.06 MiB |
data_unpacked_labeled_flip2_hydro_to_P01053.csv.jsonl |
24,935 | 5.98 MiB |
data_unpacked_labeled_flip2_hydro_to_P06241.csv.jsonl |
24,935 | 5.97 MiB |
data_unpacked_labeled_flip2_hydro_to_P0A9X9.csv.jsonl |
24,935 | 5.98 MiB |
data_unpacked_labeled_flip2_ired_two_to_many.csv.jsonl |
8,586 | 3.95 MiB |
data_unpacked_labeled_flip2_nucb_two_to_many.csv.jsonl |
55,759 | 16.85 MiB |
data_unpacked_labeled_flip2_pdz3_single_to_double.csv.jsonl |
734 | 213.50 KiB |
data_unpacked_labeled_flip2_rhomax_by_wild_type.csv.jsonl |
884 | 389.02 KiB |
data_unpacked_labeled_flip2_trpb_by_position.csv.jsonl |
228,298 | 126.97 MiB |
data_unpacked_labeled_flip2_trpb_one_to_many.csv.jsonl |
228,298 | 126.94 MiB |
data_unpacked_labeled_flip2_trpb_two_to_many.csv.jsonl |
228,298 | 126.95 MiB |
Layout
.
├── _MANIFEST.json # aggregate manifest (per-table counts)
└── tables/<source_slug>.jsonl # normalized rows (one JSON object per line)
Each line in a tables/*.jsonl file is a JSON object with at least
dataset_id, row (the raw upstream row), row_index, and source_file
fields, so every row carries its upstream provenance.
Loading
hf download LiteFold/FLIP2 --repo-type dataset --local-dir ./flip2
Programmatic streaming:
import json
from pathlib import Path
from huggingface_hub import snapshot_download
local = snapshot_download(repo_id="LiteFold/FLIP2", repo_type="dataset")
for jsonl in sorted(Path(local, "tables").glob("*.jsonl")):
with jsonl.open() as f:
for line in f:
row = json.loads(line)
... # row["row"] is the upstream record
License
See upstream FLIP repository for licensing.
Citation
Dallago C, et al. FLIP: Benchmark tasks in fitness landscape inference for proteins. NeurIPS Datasets and Benchmarks, 2021.
Provenance
Built from the local manifest entry flip2 of manifests/atlas_download_plan.json.
Pipeline source: megadata-post normalize --dataset flip2 --tables-only.
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