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parkmoll
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genetic-variants-qa

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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
pathomechanism: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
splicing_effects: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
inheritance_pattern: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
haploinsufficiency: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
therapy_review: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
vs
question_type: string
variant: string
rubrics: list<item: struct<criterion: string, name: string>>
example_id: int64
comment: string
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, 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 547, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              pathomechanism: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
              splicing_effects: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
              inheritance_pattern: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
              haploinsufficiency: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
              therapy_review: struct<template: string, rubrics: list<item: struct<name: string, criterion: string>>>
              vs
              question_type: string
              variant: string
              rubrics: list<item: struct<criterion: string, name: string>>
              example_id: int64
              comment: string

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YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

  • question_types.json: prompt template + rubrics for each question type

  • rare_variants_qa.json: specific questions, with each example defined by a question type, specific gene variant, and instance-level rubrics.

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