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Add model card

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+ ---
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+ license: mit
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+ pipeline_tag: image-to-image
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+ library_name: coreai
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+ tags:
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+ - core-ai
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+ - ios
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+ - super-resolution
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+ ---
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+
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+ # EDSR x2 for Core AI
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+
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+ EDSR (`edsr_r16f64_x2`, 1.5M parameters) from [torchSR](https://github.com/Coloquinte/torchSR), exported to Apple Core AI with the [`apple/coreai-models`](https://github.com/apple/coreai-models/tree/main/models/edsr) recipe:
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+
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+ ```sh
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+ uv run models/edsr/export.py --dtype float16 --dynamic
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+ ```
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+
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+ | Folder | Contents | Size | Platforms |
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+ | ----------------- | -------------------------------------------------------------- | ------ | ---------- |
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+ | `edsr-x2.aimodel` | `main(x)`: `x` is `[batch, 3, height, width]` RGB in 0...1, float16, batch 1–64, height and width 8–256. Returns the image at twice the size | 2.6 MB | iOS, macOS |
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+
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+ Images larger than 256 pixels are upscaled in tiles.
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+
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+ ## Use
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+
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+ With [`@react-native-ai/core-ai`](https://github.com/callstackincubator/ai/tree/main/packages/core-ai), download `edsr-x2.aimodel` into app storage, then call it with `CoreAI.runRawFunction`, or through `CoreAI.runTask('super-resolution', ...)`, which tiles and converts images for you.
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+
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+ ## License
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+
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+ torchSR and its EDSR weights are MIT licensed ([EDSR paper](https://arxiv.org/abs/1707.02921)). This repository only converts them to Core AI format.