From 6a24422d13ec7a182b46fed27952806ed940f9de Mon Sep 17 00:00:00 2001
From: Niels Rogge <niels.rogge1@gmail.com>
Date: Thu, 8 Apr 2021 07:41:06 +0000
Subject: [PATCH] Add tags

---
 README.md | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 993282b..a02f6a5 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,8 @@
 ---
 license: apache-2.0
+tags:
+- image-classification
+- timm
 datasets:
 - cifar10
 - cifar100
@@ -10,7 +13,7 @@ datasets:
 - vtab
 ---
 
-# Vision Transformer base model 
+# Vision Transformer (base-sized model) 
 
 Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 million images, 1,000 classes) at resolution 224x224. It was introduced in the paper [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929) by Dosovitskiy et al. and first released in [this repository](https://github.com/google-research/vision_transformer). However, the weights were converted from the [timm repository](https://github.com/rwightman/pytorch-image-models) by Ross Wightman, who already converted the weights from JAX to PyTorch. Credits go to him.