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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](https://www.npmjs.com/package/react-native-executorch) library. It
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includes model exported for xnnpack, as well as coreml in `.pte` format, ready
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for use in the **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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`.pte` files. For more details, see the compatibility note in the [ExecuTorch
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GitHub
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repository](https://github.com/pytorch/executorch/blob/11d1742fdeddcf05bc30a6cfac321d2a2e3b6768/runtime/COMPATIBILITY.md?plain=1#L4).
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If you work with React Native ExecuTorch, the constants from the library will
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guarantee compatibility with runtime used behind the scenes.
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compatibility is guaranteed. Older versions of the runtime may not work with
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these files.
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##
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library_name: executorch
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---
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# style-transfer-candy
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This repository hosts the **style-transfer-candy** 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: [style transfer](https://github.com/pytorch/examples/tree/main/fast_neural_style)
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## Variants
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| Path | Backend | Precision |
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| --- | --- | --- |
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| `coreml/style_transfer_candy_coreml_fp16.pte` | coreml | fp16 |
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| `xnnpack/style_transfer_candy_xnnpack_fp32.pte` | xnnpack | fp32 |
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| `xnnpack/style_transfer_candy_xnnpack_int8.pte` | xnnpack | int8 |
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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-style-transfer-candy/blob/main/mlx/NOTES.md))
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## Repository structure
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```
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LICENSE 3.4 kB
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config.json 42 B
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coreml/config.json 889 B
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coreml/style_transfer_candy_coreml_fp16.pte 3.6 MB
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mlx/NOTES.md 2.6 kB
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xnnpack/config.json 1.4 kB
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xnnpack/style_transfer_candy_xnnpack_fp32.pte 6.5 MB
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xnnpack/style_transfer_candy_xnnpack_int8.pte 1.8 MB
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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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