Vision transformer processes arbitrarily long documents with max_length=32768 via streaming API or batched inference, replacing separate page-by-page OCR pipelines.
Summary
Eliminates manual document chunking and post-processing glue code for PDF/image workflows. Single model handles both single-image and multi-page parsing with configurable inference backends (Transformers or SGLang).
Why it matters
Eliminates manual document chunking and post-processing glue code for PDF/image workflows. Single model handles both single-image and multi-page parsing with configurable inference backends (Transformers or SGLang).
Implementation verdict
Replace: page-by-page OCR loops. Requires: CUDA 12.9+, torch 2.10.0, transformers 4.57.1. Actionable now—code examples provided for Hugging Face and SGLang deployment. Pick SGLang if you need concurrent batch processing; use transformers API for simpler single-document tasks.
Sources
Dev Signal
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