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@@ -78,7 +78,6 @@ PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vi
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  * ```2025.10.29``` πŸ€— Supports calling the core module PaddleOCR-VL-0.9B of PaddleOCR-VL via the `transformers` library.
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  * ```2025.10.16``` πŸš€ We release [PaddleOCR-VL](https://github.com/PaddlePaddle/PaddleOCR), β€” a multilingual documents parsing via a 0.9B Ultra-Compact Vision-Language Model with SOTA performance.
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-
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  ## Usage
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  ### Install Dependencies
@@ -116,15 +115,25 @@ for res in output:
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  ### Accelerate VLM Inference via Optimized Inference Servers
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- 1. Start the VLM inference server (the default port is `8080`):
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- ```bash
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- docker run \
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- --rm \
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- --gpus all \
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- --network host \
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- ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddlex-genai-vllm-server
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- ```
 
 
 
 
 
 
 
 
 
 
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  2. Call the PaddleOCR CLI or Python API:
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  ```bash
@@ -133,6 +142,7 @@ for res in output:
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  --vl_rec_backend vllm-server \
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  --vl_rec_server_url http://127.0.0.1:8080/v1
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  ```
 
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  ```python
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  from paddleocr import PaddleOCRVL
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  pipeline = PaddleOCRVL(vl_rec_backend="vllm-server", vl_rec_server_url="http://127.0.0.1:8080/v1")
@@ -419,4 +429,4 @@ If you find PaddleOCR-VL helpful, feel free to give us a star and citation.
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  primaryClass={cs.CV},
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  url={https://arxiv.org/abs/2510.14528},
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  }
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- ```
 
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  * ```2025.10.29``` πŸ€— Supports calling the core module PaddleOCR-VL-0.9B of PaddleOCR-VL via the `transformers` library.
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  * ```2025.10.16``` πŸš€ We release [PaddleOCR-VL](https://github.com/PaddlePaddle/PaddleOCR), β€” a multilingual documents parsing via a 0.9B Ultra-Compact Vision-Language Model with SOTA performance.
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  ## Usage
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  ### Install Dependencies
 
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  ### Accelerate VLM Inference via Optimized Inference Servers
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+ 1. Start the VLM inference server:
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+ You can start the vLLM inference service using one of two methods:
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+
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+ - Method 1: PaddleOCR method
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+
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+ ```bash
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+ docker run \
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+ --rm \
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+ --gpus all \
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+ --network host \
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+ ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddleocr-genai-vllm-server:latest \
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+ paddleocr genai_server --model_name PaddleOCR-VL-0.9B --host 0.0.0.0 --port 8080 --backend vllm
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+ ```
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+
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+ - Method 2: vLLM method
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+
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+ [vLLM: PaddleOCR-VL Usage Guide](https://docs.vllm.ai/projects/recipes/en/latest/PaddlePaddle/PaddleOCR-VL.html)
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+
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  2. Call the PaddleOCR CLI or Python API:
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  ```bash
 
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  --vl_rec_backend vllm-server \
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  --vl_rec_server_url http://127.0.0.1:8080/v1
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  ```
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+
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  ```python
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  from paddleocr import PaddleOCRVL
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  pipeline = PaddleOCRVL(vl_rec_backend="vllm-server", vl_rec_server_url="http://127.0.0.1:8080/v1")
 
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  primaryClass={cs.CV},
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  url={https://arxiv.org/abs/2510.14528},
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  }
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+ ```