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seajohnson
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trial-travel

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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'

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Preparation pipeline: Travel / Image Text

Overview

A documented Travel data-preparation workflow for Image Text records. The bundled rows demonstrate the schema and validation path rather than pretending to be a full training corpus.

Feedback on the structure is welcome; the code is intentionally short.

Included Material

clean.py — loading, cleaning and split preparation.
dataset_infos.json — schema and split metadata.
metadata_sample.jsonl — readable records for schema checks.

Changelog

2026-10-06 — initial upload
2026-10-20 — config and docs sync

Data Sources

external sources are referenced, not redistributed
record retrieval date and filtering rules
keep provenance explicit before any training run

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.

Processing Choices

Storage format: hdf5
Preprocessing: domain specific
Augmentation: light
Split strategy: leave one out
Sampling: curriculum
Quality checks: adaptive
Labeling: self training

Intended Use

Use this repo to exercise the pipeline, adapt a documented source, or prepare controlled splits. Status: metadata sample; full source data not bundled — the sample is for schema inspection only.

Environment

Python: >= 3.9
torch: 2.x
safetensors: any recent

Files

File	Purpose
`clean.py`	primary artifact
`README.md`	this documentation
`dataset_infos.json`	schema metadata
`metadata_sample.jsonl`	schema sample

License

Distributed under the cc-by-nc-4.0 license. External datasets keep their own terms — check them separately.

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