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@ -26,7 +26,7 @@ PaddleClas的目的是为工业界和学术界提供一个图像分类任务相
<div align="center">
<img
src="docs/images/models/mobile_arm_top1.png" width="600">
src="docs/images/models/mobile_arm_top1.png" width="700">
</div>
上图展示了一些适合移动端应用的模型，在SD855上预测一张图像的CPU时间。图中MV3_large_x1_0_ssld（M是MobileNet的简称），MV3_small_x1_0_ssld、MV2_ssld和MV1_ssld，是采用PaddleClas提供的SSLD蒸馏方法训练的模型。MV3_large_x1_0_ssld_int8是进一步进行INT8量化的模型。不同模型的FLOPS、Parameters、模型存储大小，以及更多的GPU预测时间请参考文档教程中的[**模型库章节**](https://paddleclas.readthedocs.io/zh_CN/latest/zh_cn/models/models_intro.html)。