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Hugging Face
Hugging Face logoHugging Face · Feature trail

Multilingual OCR

4 posts · Apr 2026 – Aug 2026

What this trail covers

Hugging Face now supports PP-OCRv6, a highly accurate and efficient Optical Character Recognition (OCR) system capable of processing 50 languages. This system offers a range of model sizes, from 1.5 million to 34.5 million parameters, allowing for flexible deployment based on performance and resource constraints. The integration includes support for ONNX Runtime CPU backend for efficient inference. This post introduces the Dharma-AI/Dharma-OCR-LITE model, a 4B parameter image-text-to-text model, and demonstrates the integration of PaddleOCR 3.5 with the Transformers backend for OCR and document parsing tasks.

All Hugging Face trails
  1. PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M ParametersThis post introduces the PP-OCRv6 models, which support 50 languages and range in size from 1.5M to 34.5M parameters. It highlights the integration with ONNX Runtime CPU backend for efficient inference and mentions the Dharma-AI/Dharma-OCR-LITE model as an example. The post also includes a link to an online demo.
  2. PaddleOCR 3.5: Running OCR and Document Parsing Tasks with a Transformers BackendThis post demonstrates the integration of PaddleOCR 3.5 with the Hugging Face Transformers backend, enabling OCR and document parsing tasks. It highlights the use of the PaddleOCR Transformers Demo Space and showcases the ability to run OCR and document parsing with a Transformers backend, leveraging the capabilities of PaddleOCR 3.5.
  3. Same Cluster, 33 Points More Utilization: What Changed Was the OrderThis post demonstrates how reordering tasks within a cluster, specifically in the context of running OCR models like Dharma-AI/Dharma-OCR-LITE, can lead to a 33-point increase in utilization. It highlights a practical optimization achieved through intelligent task scheduling or resource management within a shared compute environment.