diff --git a/docs/zh_CN/algorithm_introduction/ImageNet_models.md b/docs/zh_CN/algorithm_introduction/ImageNet_models.md
index 6b13bd5ae5de6b64b29d645cfc810e5f61ec58fc..402c47c06afdcefbae05c5634bf7fb060ff5946e 100644
--- a/docs/zh_CN/algorithm_introduction/ImageNet_models.md
+++ b/docs/zh_CN/algorithm_introduction/ImageNet_models.md
@@ -424,13 +424,13 @@ ViT(Vision Transformer) 与 DeiT(Data-efficient Image Transformers)系列模
关于 LeViT 系列模型的精度、速度指标如下表所示,更多介绍可以参考:[LeViT 系列模型文档](../models/LeViT.md)。
-| 模型 | Top-1 Acc | Top-5 Acc | time(ms)
bs=1 | time(ms)
bs=4 | FLOPs(M) | Params(M) | 下载地址 |
-| ---------- | --------- | --------- | ---------------- | ---------------- | -------- | --------- | ------------------------------------------------------------ |
-| LeViT_128S | 0.7598 | 0.9269 | | | 281 | 7.42 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_128S_pretrained.pdparams) |
-| LeViT_128 | 0.7810 | 0.9371 | | | 365 | 8.87 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_128_pretrained.pdparams) |
-| LeViT_192 | 0.7934 | 0.9446 | | | 597 | 10.61 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_192_pretrained.pdparams) |
-| LeViT_256 | 0.8085 | 0.9497 | | | 1049 | 18.45 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_256_pretrained.pdparams) |
-| LeViT_384 | 0.8191 | 0.9551 | | | 2234 | 38.45 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_384_pretrained.pdparams) |
+| 模型 | Top-1 Acc | Top-5 Acc | time(ms)
bs=1 | time(ms)
bs=4 | FLOPs(M) | Params(M) | 预训练模型下载地址 | inference模型下载地址 |
+| ---------- | --------- | --------- | ---------------- | ---------------- | -------- | --------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| LeViT_128S | 0.7598 | 0.9269 | | | 281 | 7.42 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_128S_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/eViT_128S_infer.tar) |
+| LeViT_128 | 0.7810 | 0.9371 | | | 365 | 8.87 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_128_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/LeViT_128_infer.tar) |
+| LeViT_192 | 0.7934 | 0.9446 | | | 597 | 10.61 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_192_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/LeViT_192_infer.tar) |
+| LeViT_256 | 0.8085 | 0.9497 | | | 1049 | 18.45 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_256_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/LeViT_256_infer.tar) |
+| LeViT_384 | 0.8191 | 0.9551 | | | 2234 | 38.45 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_384_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/LeViT_384_infer.tar) |
**注**:与 Reference 的精度差异源于数据预处理不同及未使用蒸馏的 head 作为输出。