| --- |
| license: other |
| license_name: apache-license-2.0 |
| license_link: https://github.com/google/automl/blob/master/LICENSE |
| pipeline_tag: image-classification |
| library_name: executorch |
| --- |
| |
| # efficientnet-v2-s |
|
|
| This repository hosts the **efficientnet-v2-s** models exported for the |
| [React Native ExecuTorch](https://www.npmjs.com/package/react-native-executorch) |
| library as ExecuTorch `.pte` programs, ready to run on device. |
|
|
| Upstream model: [efficientnet_v2_s](https://pytorch.org/vision/0.20/models/generated/torchvision.models.efficientnet_v2_s.html#torchvision.models.efficientnet_v2_s) |
|
|
| ## Variants |
|
|
| | Path | Backend | Precision | |
| | --- | --- | --- | |
| | `coreml/efficientnet_v2_s_coreml_fp16.pte` | coreml | fp16 | |
| | `xnnpack/efficientnet_v2_s_xnnpack_fp32.pte` | xnnpack | fp32 | |
| | `xnnpack/efficientnet_v2_s_xnnpack_int8.pte` | xnnpack | int8 | |
|
|
| ## Unshipped backends |
|
|
| A backend directory carrying a `NOTES.md` and no `.pte` was exported and |
| not published. Its note records what went wrong. |
|
|
| - `mlx` ([why](https://huggingface.co/software-mansion/react-native-executorch-efficientnet-v2-s/blob/main/mlx/NOTES.md)) |
|
|
| ## Repository structure |
|
|
| ``` |
| config.json 39 B |
| coreml/config.json 840 B |
| coreml/efficientnet_v2_s_coreml_fp16.pte 41.8 MB |
| mlx/NOTES.md 2.5 kB |
| xnnpack/config.json 1.4 kB |
| xnnpack/efficientnet_v2_s_xnnpack_fp32.pte 81.7 MB |
| xnnpack/efficientnet_v2_s_xnnpack_int8.pte 21.9 MB |
| ``` |
|
|
| ## Compatibility |
|
|
| These files are published for the **ExecuTorch v1.4.1** runtime. ExecuTorch |
| gives no forward compatibility guarantee, so an older runtime may fail to load |
| them. |
|
|
| To use them in React Native ExecuTorch, pass the model constant shipped in the |
| library's model registry to the corresponding task pipeline. See the |
| [documentation](https://docs.swmansion.com/react-native-executorch/docs/fundamentals/downloading-models). |
|
|
| To load these files in your own ExecuTorch runtime, read the |
| [compatibility note](https://github.com/pytorch/executorch/blob/main/runtime/COMPATIBILITY.md) |
| first. |
|
|
