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update doc about PPHGNetV2 #3002

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update doc about PPHGNetV2 #3002

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16 changes: 13 additions & 3 deletions docs/zh_CN/models/ImageNet1k/README.md
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Expand Up @@ -12,7 +12,7 @@
- [2.3 Intel CPU 端知识蒸馏模型](#SSLD_intel_cpu)
- [三、CNN 系列模型](#CNN_based)
- [3.1 服务器端模型](#CNN_server)
- [PP-HGNet 系列](#PPHGNet)
- [PP-HGNet & PP-HGNetV2 系列](#PPHGNet)
- [ResNet 系列](#ResNet)
- [ResNeXt 系列](#ResNeXt)
- [Res2Net 系列](#Res2Net)
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<a name="PPHGNet"></a>

## PP-HGNet 系列
## PP-HGNet & PP-HGNetV2 系列

PP-HGNet 系列模型的精度、速度指标如下表所示，更多关于该系列的模型介绍可以参考：[PP-HGNet 系列模型文档](PP-HGNet.md)。
PP-HGNet & PP-HGNetV2 系列模型的精度、速度指标如下表所示，更多关于该系列的模型介绍可以参考：[PP-HGNet 系列模型文档](PP-HGNet.md)、[PP-HGNetV2 系列模型文档](PP-HGNetV2.md)。

| 模型 | Top-1 Acc | Top-5 Acc | time(ms)<br>bs=1 | time(ms)<br>bs=4 | time(ms)<br/>bs=8 | FLOPs(G) | Params(M) | 预训练模型下载地址 | inference模型下载地址 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
Expand All @@ -148,6 +148,16 @@ PP-HGNet 系列模型的精度、速度指标如下表所示，更多关于该
| PPHGNet_small_ssld | 0.8382 | 0.9681 | 2.46 | 5.12 | 8.77 | 8.53 | 24.38 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_small_ssld_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_small_ssld_infer.tar) |
| PPHGNet_base_ssld | 0.8500 | 0.9735 | 5.97 | - | - | 25.14 | 71.62 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_base_ssld_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_base_ssld_infer.tar) |

| 模型 | Top-1 Acc | Top-5 Acc | time(ms)<br>bs=1 | time(ms)<br>bs=4 | time(ms)<br/>bs=8 | FLOPs(G) | Params(M) | stage-1预训练模型下载地址 | stage-2预训练模型下载地址 |inference模型下载地址(stage-2) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| PPHGNetV2_B0 | 0.7777 | 0.9391 | 0.52 | - | - | - | - | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B0_ssld_stage1_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B0_ssld_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B0_ssld_infer.tar) |
| PPHGNetV2_B1 | 0.7918 | 0.9457 | 0.58 | - | - | - | - | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B1_ssld_stage1_pretrained.pdparams)| [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B1_ssld_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B1_ssld_infer.tar) |
| PPHGNetV2_B2 | 0.8174 | 0.9588 | 0.95 | - | - | - | - | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B2_ssld_stage1_pretrained.pdparams)| [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B2_ssld_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B2_ssld_infer.tar) |
| PPHGNetV2_B3 | 0.8298 | 0.9643 | 1.18 | - | - | - | - | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B3_ssld_stage1_pretrained.pdparams)| [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B3_ssld_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B3_ssld_infer.tar) |
| PPHGNetV2_B4 | 0.8357 | 0.9672 | 1.46 | - | - | - | - | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B4_ssld_stage1_pretrained.pdparams)| [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B4_ssld_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B4_ssld_infer.tar) |
| PPHGNetV2_B5 | 0.8475 | 0.9732 | 2.84 | - | - | - | - | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B5_ssld_stage1_pretrained.pdparams)| [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B5_ssld_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B5_ssld_infer.tar) |
| PPHGNetV2_B6 | 0.8630 | 0.9784 | 5.29 | - | - | - | - | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B6_ssld_stage1_pretrained.pdparams)| [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B6_ssld_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B6_ssld_infer.tar) |

<a name="ResNet"></a>

## ResNet 系列 <sup>[[1](#ref1)]</sup>
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