Add tags
This commit is contained in:
parent
5cfe98bea6
commit
6a24422d13
|
@ -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.
|
||||
|
||||
|
|
Loading…
Reference in New Issue