| library_name: litert | |
| base_model: timm/coat_lite_tiny.in1k | |
| tags: | |
| - vision | |
| - image-classification | |
| datasets: | |
| - imagenet-1k | |
| # coat_lite_tiny | |
| Converted TIMM image classification model for LiteRT. | |
| - Source architecture: coat_lite_tiny | |
| - File: model.tflite | |
| ## Model Details | |
| - **Model Type:** Image classification / feature backbone | |
| - **Model Stats:** | |
| - Params (M): 5.7 | |
| - GMACs: 1.6 | |
| - Activations (M): 11.6 | |
| - Image size: 224 x 224 | |
| - **Papers:** | |
| - Co-Scale Conv-Attentional Image Transformers: https://arxiv.org/abs/2104.06399 | |
| - **Dataset:** ImageNet-1k | |
| - **Original:** https://github.com/mlpc-ucsd/CoaT | |
| ## Citation | |
| ```bibtex | |
| @InProceedings{Xu_2021_ICCV, | |
| author = {Xu, Weijian and Xu, Yifan and Chang, Tyler and Tu, Zhuowen}, | |
| title = {Co-Scale Conv-Attentional Image Transformers}, | |
| booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, | |
| month = {October}, | |
| year = {2021}, | |
| pages = {9981-9990} | |
| } | |
| ``` | |