source_id stringclasses 5
values | upstream stringclasses 4
values | source_url stringclasses 5
values | archive_bytes int64 11M 11.2B | archive_sha256 stringclasses 5
values | recorded_terms stringclasses 4
values |
|---|---|---|---|---|---|
ai2d | https://prior.allenai.org/projects/diagram-understanding | https://ai2-website.s3.amazonaws.com/data/ai2d-all.zip | 990,965,374 | 1a6b77eebb8b7dbdf76a0ba6ca76c2f97ce8f81d8ee33b06593aa722e54c4786 | AI2D research-only license (non-commercial; no redistribution) |
chartqa | https://github.com/vis-nlp/ChartQA | https://huggingface.co/datasets/ahmed-masry/ChartQA/resolve/af8b6f5c08c95085271561c2a3f9d15f2b5a9031/ChartQA%20Dataset.zip?download=true | 875,370,872 | 1bf310e5a51101681495c4a24f4f29d22c4f70b52df24e2e4feb0d79cae3c160 | GPL-3.0 |
docci_annotations | https://google.github.io/docci/ | https://storage.googleapis.com/docci/data/docci_descriptions.jsonlines | 11,000,214 | c9df4819963883af35ddd2cf257949892fd8c6d88b33a012094352df60719800 | CC-BY-4.0 |
docci_images | https://google.github.io/docci/ | https://storage.googleapis.com/docci/data/docci_images.tar.gz | 7,592,938,768 | c1b1aee00856757d71cfe2cc6ab641089284276a791bfb82146b4742c59a0a1d | CC-BY-4.0 |
pubtabnet | https://github.com/ibm-aur-nlp/PubTabNet | https://huggingface.co/datasets/ajimeno/PubTabNet/resolve/06963b1af16203f4633c718e2c50109eb57ed658/pubtabnet.tar.gz?download=true | 11,244,059,914 | 90c55e733c85c98edf6d350b77f1e4c23767577555fc932e44ad723674de8d3e | CDLA-Sharing-1.0 |
Opsis V1 training data provenance
This repository records the local training-data snapshot used for opsis-v1-nano-g3. It does not contain a loadable training split, images, annotations, or generated targets. The mixed-source corpus includes AI2D, whose bundled license forbids distribution to third parties and public release of modified data. The full corpus therefore remains local.
The model card describes the checkpoint, evaluation, and CPU runtime. This page identifies the training inputs and their source terms without implying that the complete dataset can be downloaded here.
The Dataset Viewer shows five source archive metadata records: upstream URLs, archive sizes, checksums, and recorded terms. Its source_archives split is not a training or validation split.
Snapshot
| Item | Recorded value |
|---|---|
| Training rows | 100,000 |
| Validation rows | 1,000 |
| Distinct training image paths | 96,875 |
| Repeated training image rows | 3,125 |
| Distinct image files across train and validation | 97,875 |
| Local image bytes across both splits | 20,691,179,759 |
| Visually reviewed gold benchmark cases | 600 |
| Gold cases overlapping training, per curation report | 0 |
The training mix comprises 31,250 tables, 18,750 charts, 18,750 diagrams, and 31,250 ordinary images. Seventy-five thousand examples are clean images and 25,000 are PDF-style crops. The corrected chart mix includes 12,500 ChartQA and 6,250 synthetic chart examples.
PROVENANCE.md records the SHA-256 of the corrected train and validation manifests, curation reports, curator code, source archives, and model weights. It also records a SHA-256 fingerprint over the bytes of every local image file used by the two splits, in sorted relative-path order. These hashes identify the local snapshot; they do not make the restricted files available from this repository.
The row manifests currently contain machine-local absolute paths from the original training workspace. The images were verified at their corresponding locations in the current Opsis workspace. The public provenance record contains no local user path or row-level content.
Source mixture
| Source | Role | Recorded terms |
|---|---|---|
| PubTabNet | Tables | CDLA Sharing 1.0 |
| ChartQA | Charts | GPL 3.0 |
| AI2D | Diagrams | Research-only; no third-party redistribution under the bundled license |
| DOCCI | Ordinary images | CC BY 4.0 |
| Locally generated charts and diagrams | Synthetic augmentation | Project-generated; source dependencies remain subject to their terms |
This list summarizes the source metadata recorded during curation. It is not a single license grant for the mixture or the released model. Consult each upstream source before using or redistributing any part of the training corpus.
What this record verifies
The hashes can confirm that a local copy has the same row manifests, source archives, and image bytes as the recorded Opsis G3 snapshot. They do not provide the training images, make restricted material redistributable, or by themselves reproduce the checkpoint. Training also requires the base checkpoint, code, configuration, and compute environment described on the model card.
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