Instructions to use glasses/deit_tiny_patch16_224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use glasses/deit_tiny_patch16_224 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("glasses/deit_tiny_patch16_224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 563 Bytes
644ed2b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # deit_tiny_patch16_224
Implementation of DeiT proposed in [Training data-efficient image
transformers & distillation through
attention](https://arxiv.org/pdf/2010.11929.pdf)
An attention based distillation is proposed where a new token is added
to the model, the [dist]{.title-ref} token.

``` {.sourceCode .}
DeiT.deit_tiny_patch16_224()
DeiT.deit_small_patch16_224()
DeiT.deit_base_patch16_224()
DeiT.deit_base_patch16_384()
```
|