Use Hugging Face paper URL

README.md

@@ -1,17 +1,17 @@
 ---
-tags:
-- vision
-- image-classification
 datasets:
 - imagenet
-metrics:
-- accuracy
-library_tag: MogaNet
-license: apache-2.0
 language:
 - en
 library_name: timm
+license: apache-2.0
+metrics:
+- accuracy
 pipeline_tag: image-classification
+tags:
+- vision
+- image-classification
+library_tag: MogaNet
 widget:
 - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
   example_title: Tiger
@@ -19,7 +19,7 @@ widget:
 
 # Model card for moganet_xtiny_224_in1k
 
-MogaNet a new family of efficient ConvNets with preferable parameter-performance trade-offs, which is trained on ImageNet-1k (1 million images, 1,000 classes). It was first introduced in the paper [MogaNet](https://arxiv.org/abs/2211.03295) and released in [Westlake/MogaNet](https://github.com/Westlake-AI/MogaNet) and [Westlake/openmixup](https://github.com/Westlake-AI/openmixup).
+MogaNet a new family of efficient ConvNets with preferable parameter-performance trade-offs, which is trained on ImageNet-1k (1 million images, 1,000 classes). It was first introduced in the paper [MogaNet](https://huggingface.co/papers/2211.03295) and released in [Westlake/MogaNet](https://github.com/Westlake-AI/MogaNet) and [Westlake/openmixup](https://github.com/Westlake-AI/openmixup).
 
 ## Description
 
@@ -106,4 +106,4 @@ for o in output:
   year={2022},
   volume={abs/2211.03295}
 }
-```
+```