Surya Order is a vision-encoder-decoder model hosted on Hugging Face that predicts the reading order of elements in document images. It forms part of the Surya OCR project and addresses the need to reconstruct logical text flow from layouts such as multi-column pages, forms, or tables.
The model is provided in Safetensors format with 0.1 billion parameters and uses I64 and F32 tensor types. It carries a cc-by-nc-sa-4.0 license. Users load it through the Transformers library by importing AutoTokenizer and AutoModel, then calling from_pretrained on the repository vikp/surya_order with an optional device_map parameter.
Downloads reached 209070 last month. The model card lists two Spaces that incorporate it and notes that no inference provider has deployed it yet. It is delivered exclusively as a model repository on the Hugging Face platform and can be run in local environments, Colab notebooks, or Kaggle.
The repository page supplies example code for direct loading and links to relevant notebooks. No additional capabilities, integrations, or deployment options are stated.
Surya Order is an Other AI project. It focuses on determining the correct reading order of text and elements within complex document layouts for accurate OCR processing. Surya Order is an open-source project aimed at developers. The project is open source (Apache-2.0). It ships for the web and API.
Behind Surya Order is vikp, and it first shipped in 2024. The project is developed in the open on GitHub with 21.1k stars and 51 commits in the last 90 days.
Summary written by a language model from the project’s public pages.
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