Add files using upload-large-folder tool

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+1700943569813507_res101.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,65 @@
+---
+language:
+- zh
+tags:
+- hisilicon
+- hispark
+- npu
+- openharmony
+- modelzoo
+- pytorch
+---
+
+# ResNet101
+
+ResNet是ImageNet竞赛中分类问题效果较好的网络，它引入了残差学习的概念，通过增加直连通道来保护信息的完整性，解决信息丢失、梯度消失、梯度爆炸等问题，让很深的网络也得以训练。ResNet有不同的网络层数，常用的有18-layer、34-layer、50-layer、101-layer、152-layer。
+
+## Mirror Metadata
+
+- Hugging Face repo: shadow-cann/hispark-modelzoo-resnet101
+- Portal model id: h8eivmf56c00
+- Created at: 2025-09-13 18:06:31
+- Updated at: Unknown
+- Category: 计算机视觉
+
+## Framework
+
+- PyTorch
+
+## Supported OS
+
+- OpenHarmony
+- Linux
+
+## Computing Power
+
+- Hi3403V100 SVP_NNN
+- Hi3403V100 NNN
+
+## Tags
+
+- 分类
+
+## Detail Parameters
+
+- 输入: 224x224
+- 参数量: 44.496M
+- 计算量: 15.686GFLOPs
+
+## Files In This Repo
+
+- resnet101.onnx (源模型 / 源模型下载; 源模型 / 源模型元数据; 编译模型 / OM 元数据 / a8w8)
+- resnet101-63fe2227.pth (源模型 / 源模型下载; 源模型 / 源模型元数据)
+- SVP_NNN_PC_V1.0.6.0.tgz (附加资源 / 附加资源)
+
+## Upstream Links
+
+- Portal card: https://gitbubble.github.io/hisilicon-developer-portal-mirror/model-detail.html?id=h8eivmf56c00
+- Upstream repository: https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/ResNet101
+- License reference: https://github.com/pytorch/vision/blob/v0.14.0/LICENSE
+
+## Notes
+
+- This repository was mirrored from the HiSilicon Developer Portal model card and local downloads captured on 2026-03-27.
+- File ownership follows the portal card mapping, not just filename similarity.
+- Cover image: 1700943569813507_res101.png

SVP_NNN_PC_V1.0.6.0.tgz

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+size 31072256

model-card.json

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+{
+  "name": "ResNet101",
+  "id": "h8eivmf56c00",
+  "description": "ResNet是ImageNet竞赛中分类问题效果较好的网络，它引入了残差学习的概念，通过增加直连通道来保护信息的完整性，解决信息丢失、梯度消失、梯度爆炸等问题，让很深的网络也得以训练。ResNet有不同的网络层数，常用的有18-layer、34-layer、50-layer、101-layer、152-layer。",
+  "category": "计算机视觉",
+  "framework": [
+    "PyTorch"
+  ],
+  "supportOs": [
+    "OpenHarmony",
+    "Linux"
+  ],
+  "computingPower": [
+    "Hi3403V100 SVP_NNN",
+    "Hi3403V100 NNN"
+  ],
+  "tags": [
+    "分类"
+  ],
+  "repositoryUrl": "https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/ResNet101",
+  "licenseUrl": "https://github.com/pytorch/vision/blob/v0.14.0/LICENSE",
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+      {
+        "name": "参数量",
+        "value": "44.496M"
+      },
+      {
+        "name": "计算量",
+        "value": "15.686GFLOPs"
+      }
+    ],
+    "quickStart": {
+      "url": "https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/ResNet101",
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