docling.rs ML models (models-v1)

Third-party model notice

docling.rs's PDF/image pipeline uses two ONNX graphs that are format
conversions of docling-project's own PyTorch models, not weights docling.rs
trains or modifies. They're licensed separately from docling.rs's own MIT
code (see LICENSE) under their upstream terms:

Model	Source	License
RT-DETR layout model (layout_heron.onnx)	docling-project/docling-layout-heron	Apache-2.0
TableFormer (tableformer/{encoder,decoder,bbox}.onnx)	docling-project/docling-models (model_artifacts/tableformer/accurate)	CDLA-Permissive-2.0 / Apache-2.0

scripts/install/export_layout.py and scripts/install/export_tableformer.py do the
conversion (PyTorch → ONNX via torch.onnx.export); no weights are retrained,
fine-tuned, or otherwise altered. .github/workflows/publish-models.yml runs
that conversion (and re-hosts pdfium + the OCR model alongside it) and
publishes everything as GitHub Release assets on this repo (tag models-v1),
fetched by scripts/install/download_dependencies.sh — see that script and
crates/docling-node/deps.js — purely to spare downstream users the
PyTorch/transformers/docling_ibm_models toolchain needed to export them
locally.

Both upstream licenses permit redistribution with attribution; this file is
that attribution. See the linked model cards for the full license text and any
additional upstream terms.