| --- |
| library_name: litert |
| base_model: timm/maxvit_tiny_rw_224.sw_in1k |
| tags: |
| - vision |
| - image-classification |
| datasets: |
| - imagenet-1k |
| --- |
| # maxvit_tiny_rw_224 |
| |
| Converted TIMM image classification model for LiteRT. |
| |
| - Source architecture: `maxvit_tiny_rw_224` |
| - Source checkpoint: `timm/maxvit_tiny_rw_224.sw_in1k` |
| - File: `model.tflite` |
| - Input: `float32` tensor in NCHW layout, shape `[1, 3, 224, 224]` |
| - Output: ImageNet-1K logits, shape `[1, 1000]` |
|
|
| ## Runtime Status |
|
|
| - CPU smoke test: passed with LiteRT `CompiledModel`. |
| - GPU delegation: currently blocked for this model by rank-5 tensor patterns in the GPU backend, mostly `RESHAPE`, `TRANSPOSE`, and related window/attention operations. The model is published as CPU-ready while GPU support is being improved. |
|
|
| ## Model Details |
|
|
| - **Model Type:** Image classification / feature backbone |
| - **Model Stats:** |
| - Params (M): 29.1 |
| - GMACs: 5.1 |
| - Activations (M): 33.1 |
| - Image size: 224 x 224 |
| - **Papers:** |
| - MaxViT: Multi-Axis Vision Transformer: https://arxiv.org/abs/2204.01697 |
| - **Dataset:** ImageNet-1k |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{rw2019timm, |
| author = {Ross Wightman}, |
| title = {PyTorch Image Models}, |
| year = {2019}, |
| publisher = {GitHub}, |
| journal = {GitHub repository}, |
| doi = {10.5281/zenodo.4414861}, |
| howpublished = {\url{https://github.com/huggingface/pytorch-image-models}} |
| } |
| ``` |
| ```bibtex |
| @article{tu2022maxvit, |
| title={MaxViT: Multi-Axis Vision Transformer}, |
| author={Tu, Zhengzhong and Talebi, Hossein and Zhang, Han and Yang, Feng and Milanfar, Peyman and Bovik, Alan and Li, Yinxiao}, |
| journal={ECCV}, |
| year={2022}, |
| } |
| ``` |
| ```bibtex |
| @article{dai2021coatnet, |
| title={CoAtNet: Marrying Convolution and Attention for All Data Sizes}, |
| author={Dai, Zihang and Liu, Hanxiao and Le, Quoc V and Tan, Mingxing}, |
| journal={arXiv preprint arXiv:2106.04803}, |
| year={2021} |
| } |
| ``` |
|
|
|
|
