The dataset viewer is not available for this 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.
Agriculture Text Tabular Data Notes
Overview
Preparation notes and schema examples for Agriculture tasks using Text Tabular data. Full source material is intentionally not bundled, so provenance and licensing remain explicit.
Comments and corrections can be left in the discussion tab.
Included material
loader.py— loading, cleaning and split preparation.dataset_infos.json— schema and split metadata.metadata_sample.jsonl— readable records for schema checks.
Changelog
- 2026-10-19 — initial upload
- 2026-10-22 — config and docs sync
Acknowledgments
This repo borrows ideas freely from public reference implementations; credit to their authors.
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.
Processing choices
- Storage format: lmdb
- Preprocessing: adaptive
- Augmentation: autoaugment
- Split strategy: temporal
- Sampling: hard negative
- Quality checks: strict
- Labeling: manual
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 |
|---|---|
loader.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 mit. Review the source-data terms separately when this repository is used with external datasets.
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