Datasets:

AlexandreSheva
/

rukopys-curated-mvp

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
                  first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
                  fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
                                                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
                  cls = get_filesystem_class(protocol)
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
                  raise ValueError(f"Protocol not known: {protocol}")
              ValueError: Protocol not known: memory
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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RUKOPYS Curated MVP: Ukrainian Handwriting Recognition Dataset

Task-ready curated derivative of UkrainianCatholicUniversity/rukopys for Ukrainian handwritten document AI.

This dataset turns the raw RUKOPYS release into reproducible training artifacts for full-page vision-language fine-tuning, crop-level handwriting transcription, and layout detection. It was created to support an end-to-end HTR pipeline: curation, model training, inference, evaluation.

What This Dataset Enables

Full-page image-to-JSON supervised fine-tuning.
Crop-level handwritten text transcription.
YOLO-format layout detection experiments.
Region-level analysis and filtering.
Reproducible model training and dataset packaging.

metadata.jsonl: normalized page records with image metadata and region annotations.
regions.jsonl: one row per annotated region.
vlm_sft.jsonl: crop-level transcription examples.
page_sft.jsonl: full-page image-to-structured-JSON examples.
yolo/: YOLO-format layout detection dataset.
crops/: cropped region images, if exported.
_pack_manifest.json: tar-shard manifest for packed Hub uploads.

Stats

Pages: 2715
Regions: 39420
Crop SFT examples: 38832
Page SFT examples: 2330

Sources

archive: 178
dictation: 509
school: 1782
university: 246

Region Types

annotation: 1145
formula: 6174
graph: 61
handwritten: 31193
image: 130
printed: 477
table: 240

Notes

Quality weights are assigned by annotation source:

annotator: 1.0
volunteer: 0.75
auto: 0.35

Recommended Uses

Fine-tuning VLMs for Ukrainian handwritten page parsing.
Training layout detectors for handwritten document regions.
Benchmarking OCR/HTR post-processing with structured outputs.
Demonstrating a reproducible document AI pipeline from raw data to model artifacts.

Source Dataset

This dataset is derived from UkrainianCatholicUniversity/rukopys.

@dataset{rukopys_2026,
  title        = {RUKOPYS}: Ukrainian Handwritten Text Recognition Dataset,
  author       = {Dmytro Voitekh and Volodymyr Zmiivskyyi and Oleksii Molchanovskyi},
  organization = {Ukrainian Catholic University},
  year         = {2026},
  license      = {CC BY-NC-SA 4.0},
  url          = {https://huggingface.co/datasets/UkrainianCatholicUniversity/rukopys},
  note         = {First large-scale Ukrainian HTR dataset; from 1920s archival documents to 2025 school homework and exams}
}

Downloads last month: 176

Number of rows:

28,383

Estimated number of rows:

49,076

Total file size:

14.2 GB