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README.md

@@ -4,27 +4,63 @@ pipeline_tag: image-segmentation
 library_name: executorch
 ---
 
-# Introduction
-
-This repository hosts the semantic segmentation
-[DeepLabV3](https://docs.pytorch.org/vision/main/models/deeplabv3.html) models
-for the [React Native
-ExecuTorch](https://www.npmjs.com/package/react-native-executorch) library. It
-includes models exported for xnnpack in `.pte` format, ready for use in the
-**ExecuTorch** runtime.
-
-If you'd like to run these models in your own ExecuTorch runtime, refer to the
-[official documentation](https://pytorch.org/executorch/stable/index.html) for
-setup instructions.
-
-# Compatibility
-
-If you intend to use these models outside of React Native ExecuTorch, make sure
-your runtime is compatible with the ExecuTorch version used to export the `.pte`
-files. For more details, see the compatibility note in the ExecuTorch GitHub
-repository. If you work with React Native ExecuTorch, the constants from the
-library will guarantee compatibility with runtime used behind the scenes.
-
-These models were exported using **ExecuTorch** version 1.1.0 and no forward
-compatibility is guaranteed. Older versions of the runtime may not work with
-these files.
+# deeplab-v3
+
+This repository hosts the **deeplab-v3** 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: [DeepLabV3](https://docs.pytorch.org/vision/main/models/deeplabv3.html)
+
+## Variants
+
+| Path | Backend | Precision |
+| --- | --- | --- |
+| `coreml/deeplab_v3_mobilenet_v3_large_coreml_fp16.pte` | coreml | fp16 |
+| `coreml/deeplab_v3_resnet50_coreml_fp16.pte` | coreml | fp16 |
+| `coreml/deeplab_v3_resnet101_coreml_fp16.pte` | coreml | fp16 |
+| `xnnpack/deeplab_v3_mobilenet_v3_large_xnnpack_fp32.pte` | xnnpack | fp32 |
+| `xnnpack/deeplab_v3_mobilenet_v3_large_xnnpack_int8.pte` | xnnpack | int8 |
+| `xnnpack/deeplab_v3_resnet50_xnnpack_fp32.pte` | xnnpack | fp32 |
+| `xnnpack/deeplab_v3_resnet50_xnnpack_int8.pte` | xnnpack | int8 |
+| `xnnpack/deeplab_v3_resnet101_xnnpack_fp32.pte` | xnnpack | fp32 |
+| `xnnpack/deeplab_v3_resnet101_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-deeplab-v3/blob/main/mlx/NOTES.md))
+
+## Repository structure
+
+```
+config.json                                             32 B
+coreml/config.json                                      2.1 kB
+coreml/deeplab_v3_mobilenet_v3_large_coreml_fp16.pte    21.5 MB
+coreml/deeplab_v3_resnet101_coreml_fp16.pte             112 MB
+coreml/deeplab_v3_resnet50_coreml_fp16.pte              75.9 MB
+mlx/NOTES.md                                            2.0 kB
+xnnpack/config.json                                     5.0 kB
+xnnpack/deeplab_v3_mobilenet_v3_large_xnnpack_fp32.pte  42.1 MB
+xnnpack/deeplab_v3_mobilenet_v3_large_xnnpack_int8.pte  10.8 MB
+xnnpack/deeplab_v3_resnet101_xnnpack_fp32.pte           224 MB
+xnnpack/deeplab_v3_resnet101_xnnpack_int8.pte           58.9 MB
+xnnpack/deeplab_v3_resnet50_xnnpack_fp32.pte            151 MB
+xnnpack/deeplab_v3_resnet50_xnnpack_int8.pte            40.4 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/loading-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.