Dataset Viewer
The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    AttributeError
Message:      'str' object has no attribute 'items'
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 67, in compute_config_names_response
                  config_names = get_dataset_config_names(
                      path=dataset,
                      token=hf_token,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                      path,
                  ...<4 lines>...
                      **download_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1182, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1157, in dataset_module_factory
                  ).get_module()
                    ~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 692, in get_module
                  config_name: DatasetInfo.from_dict(dataset_info_dict)
                               ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/info.py", line 284, in from_dict
                  return cls(**{k: v for k, v in dataset_info_dict.items() if k in field_names})
                                                 ^^^^^^^^^^^^^^^^^^^^^^^
              AttributeError: 'str' object has no attribute 'items'

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.

Preparation pipeline: Wildlife / Image Audio

Overview

Preparation notes and schema examples for Wildlife tasks using Image Audio data. Full source material is intentionally not bundled, so provenance and licensing remain explicit.

The whole setup fits in a single module on purpose.


Roadmap

  • tighten the smoke-test entry point
  • document expected input shapes
  • add a small evaluation script

Processing Choices

Item Value
Storage format parquet
Preprocessing domain specific
Augmentation autoaugment
Split strategy kfold 5
Sampling hard negative
Quality checks adaptive
Labeling pseudo label

Included Material

  • load_data.py — loading, cleaning, and split preparation code.
  • dataset_infos.json — schema and split metadata.
  • metadata_sample.jsonl — small, human-readable records for checking the schema.
  • README.md — data card and usage notes.

Data Sources

Source material is referenced but not bundled. Record the source version, retrieval date and any filtering rule so the same rows can be reproduced later.


Intended Use

  • pipeline testing and source adaptation
  • controlled research split preparation
  • not a training corpus — schema inspection only

Risks And Limitations

The loader cannot guarantee that an external source is representative, correctly licensed, or free of sensitive information. Users remain responsible for source review, privacy checks, and bias analysis before training or redistribution.


Files

File Purpose
load_data.py primary artifact
README.md this documentation
dataset_infos.json schema metadata
metadata_sample.jsonl schema sample
examples/sample_usage.py usage sketch

License

Released under cc-by-sa-4.0. Review the source-data terms separately when this repository is used with external datasets.

Downloads last month
29