| | --- |
| | license: apache-2.0 |
| | tags: |
| | - vision |
| | - image-classification |
| | datasets: |
| | - imagenet |
| | widget: |
| | - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg |
| | example_title: Tiger |
| | - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg |
| | example_title: Teapot |
| | - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg |
| | example_title: Palace |
| | --- |
| | |
| | Google didn't publish vit-tiny and vit-small model checkpoints in Hugging Face. I converted the weights from the [timm repository](https://github.com/rwightman/pytorch-image-models). This model is used in the same way as [ViT-base](https://huggingface.co/google/vit-base-patch16-224). |
| |
|
| | Note that [safetensors] model requires torch 2.0 environment. |
