add inference model link to LeViT

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)<br>bs=1 | time(ms)<br>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)<br>bs=1 | time(ms)<br>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。