PaddleOCR 3.5: Running OCR and Document Parsing Tasks with a Transformers Backend

Summary

PaddleOCR 3.5 adds a more flexible inference-engine interface for OCR and document parsing, allowing supported models to run with a Hugging Face Transformers backend selected through engine="transformers". It keeps pipelines managed by PaddleOCR while exposing backend-specific settings such as dtype, device placement, and attention implementation through engine_config. The release supports command-line and Python usage, with examples configuring GPU execution and float32, bfloat16, or SDPA options according to hardware and deployment environment. This provides a more natural path for RAG, Document AI, search, analytics, and agent stacks centered on PyTorch and Transformers, while the default paddle_static backend is usually recommended when maximizing OCR or document parsing throughput is the priority.

Takeaways

1. 1

   The Transformers backend is selected with engine="transformers", while engine_config supports options including dtype, device placement, and attention implementation.

2. 2

   PaddleOCR continues to manage the pipelines behind supported OCR and document parsing tasks, so developers do not need to call each internal component manually.

3. 3

   The Transformers backend suits Hugging Face- and PyTorch-centered integration, but paddle_static is usually recommended when maximum OCR or document parsing throughput is the priority.