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README.md

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+---
+license: openrail++
+library_name: coreai
+pipeline_tag: image-to-image
+tags:
+  - super-resolution
+  - diffusion
+  - core-ai
+  - apple
+  - on-device
+  - adcsr
+  - stable-diffusion
+---
+
+# AdcSR ×4 Super-Resolution — Core AI
+
+On-device **×4 super-resolution** with **AdcSR** ([Adversarial Diffusion Compression](https://github.com/Guaishou74851/AdcSR),
+CVPR 2025) converted for Apple's **Core AI** stack. AdcSR compresses the one-step diffusion model
+[OSEDiff](https://github.com/cswry/OSEDiff) into a small **diffusion-GAN**: a pruned Stable
+Diffusion 2.1 UNet + a half-size VAE decoder, run in **one forward pass** — no iterative denoising,
+no prompt, no noise — so it is fast and small enough to run fully on-device, including iPhone.
+
+## What it is
+
+- **fp16, ~870 MB.** On the GPU the Core AI output matches the fp32 reference (cosine 1.000008).
+- **Image → image, one step.** Input a low-resolution tile, get a 4× tile back. No text, no noise.
+- **456 M parameters** (pruned SD-2.1 UNet + half VAE decoder).
+
+## I/O contract (per tile)
+
+- **input:** `lr` `[1,3,128,128]` in `[-1,1]` (a low-resolution tile).
+- **output:** `sr` `[1,3,512,512]` in `[-1,1]` (×4), with the reference's per-image color-match baked in.
+
+## Usage (CoreAIKit)
+
+```swift
+import CoreAIKitVision
+
+let sr = try await SuperResolver(model: .adcsrX4)   // downloads this repo on first use
+let big = try await sr.upscale(cgImage)             // ×4; tiles any-size input + feather-blends
+```
+
+`SuperResolver` splits any-size input into overlapping 128-px LR windows, runs each, and blends.
+Load uses explicit GPU specialization options (GraphModel does this) — the runtime's *default*-
+options load path has a GPU-delegate JIT bug, but an explicit `.gpu` load is clean.
+
+## License & attribution
+
+- **AdcSR** (method + the pruning/training code): Apache-2.0 — Bingchen Li et al., *Adversarial
+  Diffusion Compression for Real-World Image Super-Resolution*, CVPR 2025.
+- **Weights** are derived from **Stable Diffusion 2.1** (via OSEDiff) and therefore carry the
+  **CreativeML Open RAIL++-M** license — commercial use is permitted under its use-based
+  restrictions, the same license under which Apple distributes Stable Diffusion for Core ML.
+
+This Core AI conversion inherits both. See `LICENSE` (Apache-2.0, AdcSR) and the SD-2.1 OpenRAIL++-M
+terms.