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+ ---
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+ license: other
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+ license_name: nutrient-commercial
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+ pipeline_tag: image-text-to-text
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+ language: [multilingual]
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+ tags:
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+ - page-stream-segmentation
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+ - document-boundary-detection
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+ - document-ai
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+ - document-splitting
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+ datasets:
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+ - nutrientdocs/doc-split-benchmark
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+ ---
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+
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+ # doc-split-v2 Β· _commercial_
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+
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+ **One model that splits any document stream β€” short or long, English or not, forms or prose.** The
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+ high-accuracy flagship for page-stream segmentation: hand it a merged/scanned PDF and it marks where each
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+ new document begins. **Weights are commercial** (not downloadable here); this page is a spec + scorecard.
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+
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+ It is the document specialist in a field of generalists β€” cloud VLMs and OpenPSS's own single-slice
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+ specialists each fall down somewhere; this one does short *and* long streams with one model. For the
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+ open-weight companion, see [doc-split-v1](https://huggingface.co/nutrientdocs/doc-split-v1).
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+
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+ - 🎯 **Try it:** [doc-split-demo](https://huggingface.co/spaces/nutrientdocs/doc-split-demo?model=flagship)
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+ - πŸ† **Leaderboard:** [doc-split-leaderboard](https://huggingface.co/spaces/nutrientdocs/doc-split-leaderboard)
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+ - πŸ“Š **Benchmark:** [doc-split-benchmark](https://huggingface.co/datasets/nutrientdocs/doc-split-benchmark)
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+ - 🟒 **Open weights:** [doc-split-v1](https://huggingface.co/nutrientdocs/doc-split-v1)
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+
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+ ## Results β€” boundary F1 (ΞΊ)
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+
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+ **This model** vs the open `doc-split-v1`, the strongest cloud VLM, and prior work (bold = best releasable single model).
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+
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+ | Cut | **doc-split-v2** | doc-split-v1 (open) | best cloud VLM | OpenPSS specialist |
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+ |---|---|---|---|---|
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+ | OpenPSS-short (sparse) | **0.652** (.60) | 0.585 | 0.598 | 0.76 (short-spec) |
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+ | OpenPSS-long | **0.891** (.86) | 0.859 | 0.244 | 0.83 (long-spec) |
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+ | our-200 (synthetic) | **0.944** (.79) | 0.936 | 0.942 | β€” |
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+ | TABME++ test | **0.943** (.91) | 0.704 | β€” | β€” |
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+ | Tobacco800 test | **0.969** (.93) | 0.820 | β€” | β€” |
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+ | val (real-doc) | **0.917** (.86) | 0.918 | β€” | β€” |
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+
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+ **One balanced model, not two specialists.** OpenPSS needs a separate short- and long-specialist (each
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+ craters on the other slice); the flagship does both with one model, and its OpenPSS-**long** (0.891) tops
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+ even OpenPSS's own long-specialist (0.83) and every cloud VLM (best 0.244). It also dominates the modern
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+ TABME++/Tobacco800 benchmarks. See the [leaderboard](https://huggingface.co/spaces/nutrientdocs/doc-split-leaderboard)
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+ for the full field.
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+
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+ ## Intended use & limits
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+
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+ - **Use it for:** segmenting a stream of page images (a merged/scanned PDF) into its constituent documents β€”
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+ short or long, English or not, forms or prose. One model handles both sparse and dense boundary regimes;
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+ the embedded text layer sharpens boundaries when present, and scanned pages fall back to vision.
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+ - **Limits:** optimized for **document** page streams; confidence is calibrated on our-domain data, so very
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+ out-of-distribution scans are approximate. Boundaries only (not document *type*).
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+
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+ ## License & data
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+
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+ The model **weights** are offered under a commercial Nutrient license β€” deployed on-prem, so your documents
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+ never leave your infrastructure. The training set is not redistributed; evaluation runs on the held-out
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+ [doc-split-benchmark](https://huggingface.co/datasets/nutrientdocs/doc-split-benchmark).
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+
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+ > ### πŸ“© Get access
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+ >
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+ > `doc-split-v2` is commercial and its weights are not downloadable here. To run it on-prem β€”
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+ > one model for any stream, calibrated, private β€” **contact Nutrient:
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+ > [nutrient.io/contact-sales](https://www.nutrient.io/contact-sales/).**
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+
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+ ## About the author
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+
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+ <a href="https://nutrient.io/">
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+ <img src="https://avatars2.githubusercontent.com/u/1527679?v=3&s=200" height="80" />
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+ </a>
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+
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+ This project is maintained and funded by [Nutrient](https://nutrient.io/) - The deterministic document infrastructure enterprises run their highest-stakes workflows on: replayable output, clear exceptions, and full audit trails on the messy, regulated documents where AI alone breaks.