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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+TokForge-SDXL-Turbo-CoreML-6bit/Resources/Unet.mlmodelc/model.mil filter=lfs diff=lfs merge=lfs -text

TokForge-SDXL-Turbo-CoreML-6bit/README.md

@@ -0,0 +1,103 @@
+---
+license: other
+license_name: sai-nc-community
+license_link: https://huggingface.co/stabilityai/sdxl-turbo/blob/main/LICENSE.md
+base_model: stabilityai/sdxl-turbo
+tags:
+- coreml
+- stable-diffusion
+- sdxl-turbo
+- text-to-image
+- ane
+- apple-neural-engine
+- 6-bit
+- palettized
+- tokforge
+pipeline_tag: text-to-image
+---
+
+# TokForge-SDXL-Turbo-CoreML-6bit (batch-one, guidance-free)
+
+Core ML conversion of [stabilityai/sdxl-turbo](https://huggingface.co/stabilityai/sdxl-turbo)
+for on-device, Apple-Neural-Engine-accelerated text-to-image generation in the
+TokForge iOS app.
+
+## What this is
+
+- **SDXL-Turbo distilled** — adversarially-distilled SDXL that produces images in
+  **1-4 steps** (no long sampling schedule needed).
+- **6-bit palettized** — weights compressed with 6-bit look-up-table palettization
+  (`--quantize-nbits 6`), keeping quality high while shrinking the model for mobile.
+- **SPLIT_EINSUM attention** — the attention implementation Apple recommends so the
+  UNet runs on the **Apple Neural Engine (ANE)** rather than falling back to GPU/CPU.
+- **Batch-one / guidance-free** — the UNet is baked with a **batch size of 1**
+  (`--unet-batch-one`). This means it runs **without classifier-free guidance**:
+  one UNet evaluation per step instead of two, so it is roughly **2x faster per step**
+  than a standard batch-2 (CFG) bake. Drive it with **`guidanceScale = 1.0`** in the
+  Swift `StableDiffusionPipeline` (CFG disabled).
+- **512x512** native latent resolution (`--latent-h 64 --latent-w 64`).
+
+## Contents
+
+`Resources/` is the bundle for Apple's
+[`ml-stable-diffusion`](https://github.com/apple/ml-stable-diffusion) Swift package:
+
+| File | Role |
+|------|------|
+| `TextEncoder.mlmodelc` | CLIP text encoder 1 |
+| `TextEncoder2.mlmodelc` | CLIP text encoder 2 (SDXL) |
+| `Unet.mlmodelc` | Batch-one 6-bit UNet (ANE) |
+| `VAEDecoder.mlmodelc` | VAE decoder |
+| `vocab.json`, `merges.txt` | Tokenizer assets |
+
+The `*.mlpackage` files are the un-compiled sources kept alongside for reference.
+
+## Usage (Swift)
+
+```swift
+import StableDiffusion
+
+let pipeline = try StableDiffusionXLPipeline(
+    resourcesAt: resourcesURL,           // the Resources/ folder
+    configuration: MLModelConfiguration() // .cpuAndNeuralEngine
+)
+
+var config = StableDiffusionPipeline.Configuration(prompt: "a red sports car on a mountain road at sunset")
+config.stepCount   = 2        // 1-4 steps for SDXL-Turbo
+config.guidanceScale = 1.0    // REQUIRED: batch-one bake is guidance-free
+config.seed        = 42
+
+let images = try pipeline.generateImages(configuration: config)
+```
+
+## Performance notes
+
+- **First load incurs a one-time ANE compile (~minutes for this UNet), then it is
+  cached** on the device. Subsequent loads are fast. The TokForge app warms/prewarms
+  the ANE so users do not pay this cost at generation time.
+- On an M4 Max (CPU_AND_NE), guidance-free generation runs at roughly **~8 it/s** at
+  512x512 — about **2x** the throughput of the equivalent batch-2 (CFG) bake (~3.86 it/s),
+  because batch-one halves the per-step UNet work.
+
+## Conversion
+
+Converted with `apple/ml-stable-diffusion` `torch2coreml` on an Apple M4 Max (128 GB):
+
+```
+python -m python_coreml_stable_diffusion.torch2coreml \
+  --model-version stabilityai/sdxl-turbo --xl-version \
+  --bundle-resources-for-swift-cli \
+  --convert-unet --convert-text-encoder --convert-vae-decoder \
+  --attention-implementation SPLIT_EINSUM \
+  --quantize-nbits 6 --latent-h 64 --latent-w 64 \
+  --unet-batch-one -o out_sdxl_turbo_6bit_b1
+```
+
+Verified with 3 guidance-free render tests (`--guidance-scale 0.0 --num-inference-steps 4
+--compute-unit CPU_AND_NE`): astronaut on a horse on the moon, a corgi in a flower field,
+a red sports car at sunset — all clean (non-uniform, no NaN/black, rich color).
+
+## License
+
+Inherits the [Stability AI Non-Commercial Community License](https://huggingface.co/stabilityai/sdxl-turbo/blob/main/LICENSE.md)
+from the base SDXL-Turbo model.

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+        "name" : "hidden_embeds",
+        "type" : "MultiArray"
+      },
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+        "isOptional" : "0",
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+        "shape" : "[1, 768]",
+        "name" : "pooled_outputs",
+        "type" : "MultiArray"
+      }
+    ],
+    "version" : "stabilityai\/sdxl-turbo",
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+
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+    "author" : "Please refer to the Model Card available at huggingface.co\/stabilityai\/sdxl-turbo",
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