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4 changes: 4 additions & 0 deletions docs/version3.x/algorithm/PaddleOCR-VL/PaddleOCR-VL.en.md
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Expand Up @@ -173,3 +173,7 @@ Please refer to our usage documentation [PaddleOCR-VL Usage](../../pipeline_usag
2. How to fine-tune the PaddleOCR-VL model?

Currently, we do not support fine-tuning of the model, but it is a high-priority feature and will be released soon. Please stay tuned.

5. If the results of the layout check are not satisfactory, what solutions can be optimized?

Since layout detection is mainly trained for various document scenarios, if your test data is non-standard documents such as license plates, tickets images or ID Cards and you want to do OCR recognition, you can directly use the PaddleOCR-VL-0.9B model and turn off the layout detection model by setting use_layout_detection to False. If you find any layout detection errors, you can directly try the effect of using PaddleOCR-VL-0.9B alone.
5 changes: 5 additions & 0 deletions docs/version3.x/algorithm/PaddleOCR-VL/PaddleOCR-VL.md
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Expand Up @@ -177,3 +177,8 @@ PaddleOCR-VL能够支持多种类型的文档解析，以下是一些预测案
2. 如何对 PaddleOCR-VL 模型进行微调 ？

目前我们暂不支持模型的微调，但已经在高优的支持中，即将发布，请保持关注。


5. 如果版面检测的结果不理想，有什么方案可以优化？

由于版面检测主要针对各种文档场景训练，所以您的测试数据如果是非标准文档，如车牌，火车票或身份证图像想做OCR识别，那可以直接使用PaddleOCR-VL-0.9B的模型，通过设置 use_layout_detection 为 False 关闭版面检测模型。如果您发现有任何版面检测的错误，都可以直接尝试一下单独使用PaddleOCR-VL-0.9B的效果。