docs: model card

README.md

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+---
+library_name: onnxruntime
+pipeline_tag: object-detection
+license: mit
+base_model: microsoft/table-transformer-detection
+tags:
+  - table-detection
+  - table-structure-recognition
+  - tatr
+  - table-transformer
+  - onnx
+  - gmft
+---
+
+# Microsoft Table Transformer (TATR) — ONNX re-export
+
+Re-export of Microsoft's Table Transformer to ONNX, packaged the way [GMFT](https://github.com/conjuncts/gmft) consumes it. Used by [ScanIndex](https://github.com/welcomyou/scanindex) for table detection + structure recognition during DOCX export.
+
+## Variants
+
+| Subdir | Upstream | Task |
+|---|---|---|
+| `gmft_onnx/detection/model.onnx` | [`microsoft/table-transformer-detection`](https://huggingface.co/microsoft/table-transformer-detection) | Detect table bounding boxes on a page |
+| `gmft_onnx/structure/model.onnx` | [`microsoft/table-transformer-structure-recognition-v1.1-all`](https://huggingface.co/microsoft/table-transformer-structure-recognition-v1.1-all) | Detect rows / columns / cells inside a cropped table |
+
+Each subdir also contains the HF `config.json` + preprocessor metadata so `transformers` / `optimum` can wrap the ONNX directly.
+
+## Loading
+
+```python
+from huggingface_hub import snapshot_download
+local = snapshot_download("welcomyou/gmft-tatr-onnx", local_dir="models")
+# Detection:  f"{local}/gmft_onnx/detection/model.onnx"
+# Structure:  f"{local}/gmft_onnx/structure/model.onnx"
+```
+
+## Re-export reproduction
+
+See [train-convert/gmft/convert/export_gmft_tatr_to_onnx.py](https://github.com/welcomyou/scanindex/blob/main/train-convert/gmft/convert/export_gmft_tatr_to_onnx.py).
+
+## License
+
+MIT, inherited from Microsoft Table Transformer.