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README.md

@@ -17,9 +17,9 @@ Swin-Transformer是针对于图片处理设计的基于Transformer架构的神
 ## Mirror Metadata
 
 - Hugging Face repo: shadow-cann/hispark-modelzoo-swin-transformer
-- Portal model id: j3m873lcso00
-- Created at: 2026-03-16 19:19:28
-- Updated at: 2026-03-26 09:35:38
+- Portal model id: ko3ugg54j400
+- Created at: 2026-08-26 16:38:28
+- Updated at: 2026-09-01 16:13:06
 - Category: 计算机视觉
 
 ## Framework
@@ -48,16 +48,15 @@ Swin-Transformer是针对于图片处理设计的基于Transformer架构的神
 
 ## Files In This Repo
 
-- swin_om-A8W8.om (编译模型 / A8W8)
-- swin.om (编译模型 / FP16; 编译模型 / OM 元数据 / A8W8)
+- swin.om (编译模型 / A8W8; 编译模型 / OM 元数据 / A8W8)
 - swin.onnx (源模型 / 源模型下载; 源模型 / 源模型元数据)
 - swin_tiny_patch4_window7_224.pth (源模型 / 源模型下载; 源模型 / 源模型元数据)
 - swin_sim.onnx (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)
+- SVP_NNN_PC_V1.0.6.0.tgz (工具链 / 工具链)
 
 ## Upstream Links
 
-- Portal card: https://gitbubble.github.io/hisilicon-developer-portal-mirror/model-detail.html?id=j3m873lcso00
+- Portal card: https://gitbubble.github.io/hisilicon-developer-portal-mirror/model-detail.html?id=ko3ugg54j400
 - Upstream repository: https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/Swin-Transformer
 - License reference: https://github.com/microsoft/Swin-Transformer/blob/main/LICENSE
 

model-card.json

@@ -1,6 +1,6 @@
 {
   "name": "Swin-Transformer",
-  "id": "j3m873lcso00",
+  "id": "ko3ugg54j400",
   "description": "Swin-Transformer是针对于图片处理设计的基于Transformer架构的神经网络。该网络针对原始Transformer迁移到图片端后计算量过大，复用困难的问题，提出了新的swin-block以代替原有的attention架构。模型以窗口的attention方式极大地减少了图像不同区域间的互相响应，同时也避免了部分冗余信息的产生。最终，模型在减少了大量计算量的同时，在不同的视觉传统任务上也有了效果的提升。",
   "category": "计算机视觉",
   "framework": [
@@ -20,16 +20,10 @@
   "repositoryUrl": "https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/Swin-Transformer",
   "licenseUrl": "https://github.com/microsoft/Swin-Transformer/blob/main/LICENSE",
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-      ]
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     {
       "fileName": "swin.om",
       "variants": [
-        "编译模型 / FP16",
+        "编译模型 / A8W8",
         "编译模型 / OM 元数据 / A8W8"
       ]
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@@ -57,22 +51,22 @@
     {
       "fileName": "SVP_NNN_PC_V1.0.6.0.tgz",
       "variants": [
-        "附加资源 / 附加资源"
+        "工具链 / 工具链"
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-    "id": "j3m873lcso00",
+    "id": "ko3ugg54j400",
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-    "betaVersionDesc": "Hi3403V100 NNN引擎上模型性能待进一步优化",
+    "isBeta": 0,
+    "betaVersionDesc": "",
     "description": "Swin-Transformer是针对于图片处理设计的基于Transformer架构的神经网络。该网络针对原始Transformer迁移到图片端后计算量过大，复用困难的问题，提出了新的swin-block以代替原有的attention架构。模型以窗口的attention方式极大地减少了图像不同区域间的互相响应，同时也避免了部分冗余信息的产生。最终，模型在减少了大量计算量的同时，在不同的视觉传统任务上也有了效果的提升。",
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@@ -151,7 +145,7 @@
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@@ -183,13 +177,13 @@
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@@ -246,7 +240,7 @@
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@@ -347,7 +341,7 @@
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