---
license: apache-2.0
tags:
- onnx
- document-parsing
- layout-analysis
- ocr
- table-structure-recognition
- formula-recognition
---

# docparser-models

ONNX exports of PaddlePaddle document models, one flat file per model.
`MANIFEST.txt` lists the sha256 of every file. All files are Apache-2.0.

| File | Model | Source |
| --- | --- | --- |
| `PP-DocLayoutV3_fp32_batchable.onnx` | layout detection | [`PaddlePaddle/PP-DocLayoutV3_onnx`](https://huggingface.co/PaddlePaddle/PP-DocLayoutV3_onnx), output reshaped to `[B,300,7]` |
| `PP-OCRv6_{tiny,small,medium}_det.onnx` | text detection | [`PaddlePaddle/PP-OCRv6_*_det_onnx`](https://huggingface.co/PaddlePaddle), unchanged |
| `PP-OCRv6_{tiny,small,medium}_rec_ctc.onnx` | text recognition | [`PaddlePaddle/PP-OCRv6_*_rec_onnx`](https://huggingface.co/PaddlePaddle), plus `ctc_idx` / `ctc_prob` outputs (argmax and max over the class axis) |
| `SLANet_plus_encoder.onnx`, `SLANet_plus_decoder.bin` | table structure | [`PaddlePaddle/SLANet_plus_onnx`](https://huggingface.co/PaddlePaddle/SLANet_plus_onnx): the encoder graph, and the GRU decoder's weights as raw float32 |
| `PP-FormulaNet_plus-{M,S}_{encoder,prep,decoder_step}.onnx`, `_tokenizer.json` | formula recognition | [`PaddlePaddle/PP-FormulaNet_plus-M`](https://huggingface.co/PaddlePaddle/PP-FormulaNet_plus-M) / [`-S`](https://huggingface.co/PaddlePaddle/PP-FormulaNet_plus-S), split into encoder, cross-attention precompute and one greedy decoder step over a static KV cache |
| `PP-DocLayoutV3_fp32_batchable_fp16.onnx`, `PP-OCRv6_{tiny,small,medium}_rec_ctc_fp16.onnx` | FP16 graphs for ONNX Runtime's TensorRT provider | derived from the FP32 file of this repository by `convert_fp16.py` (onnx 1.21.0, onnxconverter-common 1.16.0; I/O stay FP32) |

Pre- and post-processing follow each source model's `inference.yml`.