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README.md
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library_name: executorch
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---
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#
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This repository hosts the
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ExecuTorch
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includes models exported for xnnpack in `.pte` format, ready for use in the
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**ExecuTorch** runtime.
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[official documentation](https://pytorch.org/executorch/stable/index.html) for
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setup instructions.
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#
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library_name: executorch
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---
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# selfie-segmentation
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This repository hosts the **selfie-segmentation** models exported for the
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[React Native ExecuTorch](https://www.npmjs.com/package/react-native-executorch)
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library as ExecuTorch `.pte` programs, ready to run on device.
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Upstream model: [selfie segmentation](https://ai.google.dev/edge/mediapipe/solutions/vision/image_segmenter)
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## Variants
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| Path | Backend | Precision |
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| --- | --- | --- |
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| `coreml/selfie_segmentation_coreml_fp16.pte` | coreml | fp16 |
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| `coreml/selfie_segmentation_landscape_coreml_fp16.pte` | coreml | fp16 |
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| `xnnpack/selfie_segmentation_xnnpack_fp32.pte` | xnnpack | fp32 |
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| `xnnpack/selfie_segmentation_landscape_xnnpack_fp32.pte` | xnnpack | fp32 |
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## Unshipped backends
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A backend directory carrying a `NOTES.md` and no `.pte` was exported and
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not published. Its note records what went wrong.
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- `mlx` ([why](https://huggingface.co/software-mansion/react-native-executorch-selfie-segmentation/blob/main/mlx/NOTES.md))
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## Repository structure
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```
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config.json 41 B
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coreml/config.json 1.4 kB
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coreml/selfie_segmentation_coreml_fp16.pte 601 kB
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coreml/selfie_segmentation_landscape_coreml_fp16.pte 601 kB
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mlx/NOTES.md 2.4 kB
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xnnpack/config.json 1.4 kB
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xnnpack/selfie_segmentation_landscape_xnnpack_fp32.pte 463 kB
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xnnpack/selfie_segmentation_xnnpack_fp32.pte 486 kB
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```
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## Compatibility
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These files are published for the **ExecuTorch v1.4.1** runtime. ExecuTorch
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gives no forward compatibility guarantee, so an older runtime may fail to load
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them.
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To use them in React Native ExecuTorch, pass the model constant shipped in the
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library's model registry to the corresponding task pipeline. See the
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[documentation](https://docs.swmansion.com/react-native-executorch/docs/fundamentals/loading-models).
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To load these files in your own ExecuTorch runtime, read the
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[compatibility note](https://github.com/pytorch/executorch/blob/main/runtime/COMPATIBILITY.md)
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first.
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