road weights

Line readers and word-boundary models for the road handwritten-line transcription pipeline.

Licence: Apache-2.0 8 models Γ— 5 folds 7 word-boundary models safetensors 63.5 GB

What's inside: 8 models Γ— 5 folds, 7 word-boundary models, 63.5 GB

⚑ Quick start

This repository is public and ungated: downloads need no Hugging Face account or token. With the accompanying road code:

bash install.sh                                      # install the pinned environments
bash scripts/01_get_weights.sh --release bundle-001  # download and verify inference weights and bases
bash run_inference.sh --release bundle-001           # write outputs/submission/final_submission.csv

The downloader uses the immutable weight revision 96fa774b66a32e30f48bbe920121bcdff0548a19. It also downloads the two Qwen base models from the pinned repositories listed below. To acquire the starting models for training, including the Kraken base hosted under upstream/:

bash scripts/01_get_weights.sh --release bundle-001 --training --bases-only

πŸ“¦ Contents

Release bundle-001. Each reader comes in five versions, one per fold (f0–f4).

Folder Model Input Format Size
qwen3vl_strip/ Qwen3-VL 8B single strip LoRA adapter 3.7 GB
qwen3vl_nine/ Qwen3-VL 8B nine views LoRA adapter 3.7 GB
qwen35_strip/ Qwen3.5-9B single strip adapter 2.8 GB
qwen35_nine/ Qwen3.5-9B nine views adapter 2.8 GB
lighton_strip/ LightOnOCR-2 1B single strip full checkpoint 20.2 GB
lighton_nine/ LightOnOCR-2 1B nine views full checkpoint 20.2 GB
convnext_large/ ConvNeXt-large CTC single strip full checkpoint 4.2 GB
kraken_medium/ Kraken medium CTC single strip full checkpoint 0.3 GB
segmenter/ 2 word counters + 5 boundary finders single strip full checkpoints 5.6 GB
upstream/ PP-OCRv6 (medium), byte-identical copy – original file 64 MB

Adapters load on their public base model, downloaded from its own repository at a pinned revision. Full checkpoints need nothing else.

Pinned base models
Base Revision Used for
unsloth/Qwen3-VL-8B-Instruct-unsloth-bnb-4bit b5b904c3fcdc7541adf2a2bb219b0ed95288c794 loading qwen3vl_*
Qwen/Qwen3.5-9B c202236235762e1c871ad0ccb60c8ee5ba337b9a loading qwen35_*
lightonai/LightOnOCR-2-1B-base c1bc8eb6625be7b34178ff53481b242f7b8ffcb8 training only
timm/convnext_large.fb_in22k_ft_in1k dc2e53fad264aa1fb4e5940e0d1c9b79ac6e0854 training only
PP-OCRv6 (medium), copy in upstream/ Zenodo record 21788410 training only

πŸ”’ Integrity

manifest.json lists the size and SHA-256 of every file. The downloader checks each file against it and refuses any mismatch. Files never change within a release.

βš–οΈ Licences

The reader and word-boundary checkpoints are modified versions of the models below. The Kraken base under upstream/ is an unchanged copy.

Folders Built on Licence Credit
qwen3vl_* Qwen3-VL-8B-Instruct, 4-bit by Unsloth Apache-2.0 Qwen team, Alibaba Cloud
qwen35_* Qwen3.5-9B Apache-2.0 Qwen team, Alibaba Cloud (Β© 2026 Alibaba Cloud)
lighton_* LightOnOCR-2-1B-base Apache-2.0 LightOn
convnext_large/, segmenter/ ConvNeXt-large, via timm Apache-2.0; original weights MIT Liu et al., "A ConvNet for the 2020s" (2022); Β© Meta Platforms, Inc. and affiliates
kraken_medium/, upstream/ PP-OCRv6 (medium) Apache-2.0 Benjamin Kiessling (ALMAnaCH, Inria Paris)

Full texts: LICENSE (Apache-2.0) and licenses/MIT-ConvNeXt.txt.

πŸ™ Credits

Using the Kraken files? Please cite kraken and credit the dataset providers listed on the PP-OCRv6 record.

Runs with

Each environment has its own hash-locked pins in the road code (install/locks/<environment>.lock). CUDA 12.8 builds.

Environment Python Key packages Loads
core 3.10.12 huggingface-hub 0.36.2, numpy 2.2.6, rapidfuzz 3.14.5 download, weighted vote
seg 3.11.13 torch 2.10.0, timm 1.0.28, opencv-python-headless 4.14 segmenter/, convnext_large/
kraken 3.11.13 torch 2.10.0, kraken 7.1.1, kenlm 0.3.0 kraken_medium/
qwen3vl 3.11.13 torch 2.11.0, transformers 5.5.0, peft 0.20.0, unsloth 2026.9.2, bitsandbytes 0.50.2 qwen3vl_*
qwen35 3.11.13 torch 2.10.0, transformers 5.17.0, peft 0.19.1 qwen35_*
lighton 3.11.13 torch 2.10.0, transformers 5.17.0 lighton_*
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