Public release

.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,103 @@
+---
+license: other
+license_name: nutrient-commercial
+pipeline_tag: image-text-to-text
+tags:
+- document-ai
+- grounding
+- document-classification
+- document-split
+- open-vocabulary
+---
+
+# nutrient-document-decision · _commercial_
+
+**A decision model for documents.** In the spirit of general decision-making systems like Jev,
+`nutrient-document-decision` reads a document once and answers typed, calibrated questions about
+it — yes/no, pick-one, or scored — rather than generating free text. It's built with a particular
+focus on document and multimodal understanding: grounding (is a claim actually supported by a
+source), document classification (open-vocabulary, image+OCR), and document-split (page-stream
+boundary detection) are the tasks we benchmark today, not the limit of what the typed-decision
+interface can express — it has also shown promising zero-shot generalization to adjacent judgment
+tasks it was never trained on, such as judging which of two OCR outputs is more accurate, and
+combined classification-plus-split questions asked together in one pass.
+
+- 🎯 **Try it:** [nutrient-document-decision-demo](https://huggingface.co/spaces/nutrientdocs/nutrient-document-decision-demo)
+- 🏆 **Leaderboards:** [grounding](https://huggingface.co/spaces/nutrientdocs/grounding-leaderboard) ·
+  [document classification](https://huggingface.co/spaces/nutrientdocs/document-classification-leaderboard) ·
+  [open-vocabulary classification](https://huggingface.co/spaces/nutrientdocs/doc-openvocab-leaderboard) ·
+  [document split](https://huggingface.co/spaces/nutrientdocs/doc-split-leaderboard)
+
+## Results
+
+Every task is scored against: this model, the existing Nutrient specialist purpose-built and
+separately trained for that one task, and a general-purpose vision-language model run zero-shot
+(no fine-tuning, no task-specific calibration) — the floor any document-AI product has to clear.
+
+<!-- RESULTS-TABLE:START -->
+### Grounding
+
+| | **nutrient-document-decision** | specialist ([grounding-en](https://huggingface.co/nutrientdocs/grounding-en) / [grounding-multilingual](https://huggingface.co/nutrientdocs/grounding-multilingual)) | general-purpose VLM (zero-shot) |
+|---|---|---|---|
+| en AUC | **0.9231** | 0.8815 | 0.8306 |
+| multi AUC | 0.9485 | **0.9652** | 0.8748 |
+
+### Document classification (image + OCR)
+
+| Track | **nutrient-document-decision** | specialist ([document-classification-v2](https://huggingface.co/nutrientdocs/document-classification-v2)) | general-purpose VLM (zero-shot) |
+|---|---|---|---|
+| doclaynet macroF1 | 0.914 | **0.968** | 0.814 |
+| forms macroF1 | 0.997 | **1.000** | **1.000** |
+| OOD macroF1 (unseen doc types) | 0.632 | **0.946** | 0.795 |
+| OOV macroF1 (unseen label wording) | 0.812 | **0.830** | 0.810 |
+| Tobacco3482 macroF1 | **0.940** | 0.735 | 0.888 |
+
+### Open-vocabulary / figure classification
+
+| Track | **nutrient-document-decision** | specialist ([doc-img-classification](https://huggingface.co/nutrientdocs/doc-img-classification)) | general-purpose VLM (zero-shot) |
+|---|---|---|---|
+| broad (top1, ~48-label taxonomy) | **0.911** | 0.880 | 0.744 |
+| specialized (in-domain) top1 | **0.827** | 0.713 | 0.492 |
+| synonym (label-wording robustness) top1 | **0.833** | 0.730 | 0.740 |
+
+### Document split (page-stream segmentation)
+
+| Stream | **nutrient-document-decision** | specialist ([doc-split-v2](https://huggingface.co/nutrientdocs/doc-split-v2)) | general-purpose VLM (zero-shot) |
+|---|---|---|---|
+| our200 F1 | **0.962** | 0.944 | 0.792 |
+| OpenPSS-short F1 | **0.683** | 0.652 | 0.369 |
+| OpenPSS-long F1 | **0.959** | 0.891 | 0.482 |
+<!-- RESULTS-TABLE:END -->
+
+This model mostly beats or ties the specialist across grounding, document-split, and figure
+classification, and trails on a few document-classification tracks — notably OOD (unseen document
+types) and multilingual grounding, where a purpose-built specialist still has an edge. See the
+leaderboards linked above for the full, independently-reproducible picture against other systems.
+
+## Intended use & limits
+
+Built as a decision model for document-heavy workflows (contracts, filings, forms, mixed-format
+page streams) where a single calibrated pass needs to answer several different typed questions
+about the same document — not limited to the four tasks benchmarked above. Not a general-purpose
+chat or reasoning assistant — it reads out typed judgments (yes/no, label choice, numeric score)
+rather than generating free text, and its judgment on domains very different from its benchmark
+coverage (e.g. truly novel, unseen document types) should be validated before relying on it
+unsupervised.
+
+## License & data
+
+Commercial. Benchmarked against publicly available document-AI evaluation sets (see the linked
+leaderboards and benchmark datasets for exact sources and licenses per track).
+
+> ### 📩 Get access
+>
+> `nutrient-document-decision` is commercial and its weights are not downloadable here. To run it
+> on-prem — **contact Nutrient: [nutrient.io/contact-sales](https://www.nutrient.io/contact-sales/).**
+
+## About the author
+
+<a href="https://nutrient.io/">
+  <img src="https://avatars2.githubusercontent.com/u/1527679?v=3&s=200" height="80" />
+</a>
+
+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.