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: TypeError
Message: Couldn't cast array of type
struct<dataUsage: string, dataType: string, source: string, subset: list<item: string>, sourceUri: string, fileType: string, dataFormat: string, dataSize: double, volume: int64, volumeUnit: string, dataQuantity: int64, items: int64, owner: string>
to
{'dataUsage': Value('string'), 'dataType': Value('string'), 'source': Value('string'), 'sourceUri': Value('string'), 'fileType': Value('string'), 'dataFormat': Value('string'), 'dataSize': Value('float64'), 'volume': Value('int64'), 'volumeUnit': Value('string'), 'dataQuantity': Value('int64'), 'owner': Value('string'), 'subset': List(Value('string'))}
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
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 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2059, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2109, in cast_array_to_feature
casted_array_values = _c(array.values, feature.feature)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2149, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<dataUsage: string, dataType: string, source: string, subset: list<item: string>, sourceUri: string, fileType: string, dataFormat: string, dataSize: double, volume: int64, volumeUnit: string, dataQuantity: int64, items: int64, owner: string>
to
{'dataUsage': Value('string'), 'dataType': Value('string'), 'source': Value('string'), 'sourceUri': Value('string'), 'fileType': Value('string'), 'dataFormat': Value('string'), 'dataSize': Value('float64'), 'volume': Value('int64'), 'volumeUnit': Value('string'), 'dataQuantity': Value('int64'), 'owner': Value('string'), 'subset': List(Value('string'))}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.
Guide: How to share your data on the BoAmps repository
This guide explains step by step how to share BoAmps format reports on this public Hugging Face repository.
Prerequisites
Before starting, make sure you have:
- A Hugging Face account
- The files you want to upload
Method 1: Hugging Face Web Interface
Log in to Hugging Face
Go to the boamps dataset
Navigate to the files: Click on "Files and versions" then on the "data" folder
Click on "Contribute" then "Upload files"
Drop your files in BoAmps format (please name them clearly) and give a name to the PR (e.g. 10 reports on image classification). You can add an extended description but this is optional. The name of the files should follow this format : "report_<publisher>_<taskStage>_<taskFamily>_<infraType>_<reportID>.json"
- <publisher>: the name of the publisher (this can be useful for gathering reports written by the same person, but you can of course create a pseudonym if you wish to remain anonymous)
- <taskStage>: mandatory field of the report
- <taskFamily>: mandatory field of the report
- <infraType>: mandatory field of the report
- <reportID>: optionnal
- At the bottom of the page, click on "Open a Pull Request".
- You should see your PR created in "Community" > "Pull request". Now just wait for our team to validate your PR, thank you very much for your participation and your commitment to more frugal AI, in full transparency!
Method 2: Git (Command Line)
- Clone the repository
- Create a branch
- Add your files
- Create a PR
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