加速 Document AI：Hugging Face 提升多模態文件理解模型的推論效率
Original: Accelerating Document AI
"Document AI" is a key driver of enterprise digital transformation in recent years, aimed at automating the processing of unstructured…
本文探討 Hugging Face 在文件 AI（Document AI）領域的加速方案。針對 LayoutLMv3 與免 OCR 的 Donut 等多模態模型，Hugging Face 介紹了如何利用 Optimum 庫、ONNX Runtime 及量化技術，克服多模態模型在生產環境中的高延遲與高成本挑戰，實現高效能的文件自動化處理。
"Document AI" is a key driver of enterprise digital transformation in recent years, aimed at automating the processing of unstructured documents such as invoices, receipts, contracts, and academic papers. Traditional OCR can only recognize characters, whereas modern Document AI models (such as Microsoft's LayoutLMv3 or NAVER's Donut) fuse text, images, and layout geometry information (multimodal) to perform deep semantic understanding and structured data extraction.
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