Publish owner-selected H5.1 as v1.5 with qualified CUDA profile and preserved tradeoffs
6536f3b verified | library_name: transformers | |
| license: apache-2.0 | |
| pipeline_tag: object-detection | |
| base_model: docling-project/docling-layout-heron | |
| base_model_relation: finetune | |
| tags: | |
| - document-layout-analysis | |
| - finance | |
| - rtdetr-v2 | |
| - cuda | |
| - tf32 | |
| # AX-DocLayout-M v1.5 - H5.1 CUDA / cuDNN TF32 | |
| This is the owner-selected **H51-title final-1024 EMA** model. It continues | |
| H5 finance fine-tuning with a paired Title-sampling study. It is a separate | |
| Heron-derived model identity, not D5/D6/H7, not the public eleven-class v1.0 | |
| model, and not an ax-doclayout Python package release. The original v1.4 weights | |
| and public v1.0 loader pin remain unchanged. | |
| Decoded RGB page raster in; layout boxes out. Native classes0-16 map to AX PDF | |
| SDK IDs1-17 via `sdk-taxonomy.json` (ax-document-unified-25/1). SDK18-25 are | |
| unsupported. This model does not open PDFs, perform OCR or infer reading order. | |
| Accuracy retention of extra SDK classes12-17 is unmeasured. | |
| ## Exact artifact and qualified runtime | |
| - FP32 safetensors SHA256: | |
| `d0949704220ee50d94359cb6417e3481ac4ef5078a9f63795989e9f5d76e9b7e`. | |
| - H51-title final1024 checkpoint SHA256: | |
| `44b75b2ca14d7d4756ca51d402d470d069f17ee99145717e1994549b32ef87d2`. | |
| - Upstream: docling-project/docling-layout-heron at immutable revision | |
| `8f39ad3c0b4c58e9c2d2c84a38465abf757272d8`, Apache-2.0. | |
| - Native **640x640 direct resize**, original hash-pinned image processor. | |
| Do not substitute D5's1024letterbox or H7's1696letterbox preprocessing. | |
| - Tested CUDA: PyTorch2.12.1+cu129, CUDA12.9, Transformers4.53.3, | |
| RTX PRO6000Blackwell. FP32 storage/activations, no autocast or quantization. | |
| - **cuDNN TF32 allowed; CUDA matmul TF32 disabled.** The suffix means cuDNN | |
| permission, not all-matmul TF32. No ONNX or TensorRT artifact is included. | |
| - The exact selected checkpoint has existing three-panel CUDA evidence and | |
| exact exported-tensor reload evidence. The packaged example is CPU-qualified; | |
| it was not freshly rerun on CUDA for this publication. No GPU was restarted. | |
| ## Measured results and accepted tradeoffs | |
| All AP values are percentages on previously exposed development panels. | |
| | Panel | H5 | Matched control | Selected H5.1 / v1.5 | | |
| |---|---:|---:|---:| | |
| | General AP (6489pages) |70.6572|71.1214|71.5327| | |
| | Financial AP (1745pages) |61.5113|61.5445|61.7331| | |
| | FinTab AP (256pages) |91.5856|91.7371|91.5774| | |
| | General Title AP |35.9637|37.0977|38.7453| | |
| | General Title precision at0.30/IoU0.50 |38.9333|39.5833|36.2069| | |
| | General Title recall at0.30/IoU0.50 |48.8294|50.8361|56.1873| | |
| | FinTab AP90 |89.0473|89.0155|88.4481| | |
| Title AP treatment-control improves1.6476pp, with a paired family-bootstrap95% | |
| interval[0.4851,2.8212]. Compared with H5 at the fixed threshold,22additional | |
| true Titles accompany67additional false Titles. **The frozen numerical screen | |
| failed**, including the2pp Title AP target, Title precision retention and table | |
| AP90 retention. The owner accepted these tradeoffs and explicitly selected | |
| publication; the original screen has not been reclassified as passed. | |
| Financial is a subset of General, not independent HKEX evidence. Family | |
| independence, independent final-test quality, second-seed reproducibility and | |
| extra-class accuracy are not established. This is not a claim of overall | |
| superiority to D5, D6 or H7; their differently defined panels cannot be ranked | |
| by subtracting historical scores. See evaluation.json and the frozen screen. | |
| ## Installation and inference | |
| Use Python3.12/3.13. Install CUDA PyTorch separately for the recorded runtime: | |
| ```bash | |
| python -m pip install torch==2.12.1 --index-url https://download.pytorch.org/whl/cu129 | |
| python -m pip install -r requirements.txt | |
| ``` | |
| Download this private repository with an authorized Hugging Face account. Pin | |
| the immutable commit from the release receipt, or resolve tag `v1.5` to that | |
| commit and use `hf download --revision <COMMIT>`. The example fails closed on | |
| core hash or runtime mismatches and never falls back silently from CUDA. | |
| ```bash | |
| python predict_image.py --model-dir . --image page.png --output layout.json --device cuda | |
| ``` | |
| Use `--device cpu` explicitly for CPU. Boxes use original raster pixel xyxy | |
| coordinates and SDK class IDs1-17. The default score threshold is0.30; it is an | |
| operating point, not COCO AP/AR100. Keep all17classes when interpreting output. | |
| Do not load this artifact through the eleven-class v1.0 receipt-pinned loader. | |
| The bundle contains inference files, aggregate numeric evidence, attribution | |
| and hash receipts only. No training documents, pixels, per-page predictions, | |
| optimizer states, credentials or private training implementation are included. | |