license: openrail++
base_model: ByteDance/SDXL-Lightning
pipeline_tag: text-to-image
tags:
- core-ml
- coreml
- stable-diffusion
- apple-silicon
- ios
- quantized
ByteDance SDXL-Lightning — Core ML (8-bit)
Generated on-device from this exact Core ML build (4 steps, guidance 0, trailing timestep spacing, 1024x1024, seed 42 — 38 s on an M3 Ultra).
Not a style fine-tune — a few-step distillation of SDXL base, so it inherits base SDXL's look. Pick it for speed.
Core ML conversion for Apple silicon (iOS / iPadOS / macOS, Neural Engine), built with Apple's ml-stable-diffusion for mindfire-image.
Original model
Converted from ByteDance/SDXL-Lightning — go there for the original weights, full model card and licence.
Demo prompt
The prompt and settings used for this model's demo image (also the reference example shipped in mindfire-image):
Prompt
A girl smiling
| Setting | Value |
|---|---|
| Steps | 4 |
| Guidance (CFG) | 0.0 |
| Size | 1024x1024 |
Guidance must be 0 (CFG disabled) and the scheduler needs trailing timestep spacing. 2-8 steps.
Modifications from the base model
Converted from PyTorch/diffusers to Core ML (.mlmodelc) and quantized to 8-bit palettized
weights. No fine-tuning — behaviour tracks the base model, though quantization can shift outputs
slightly.
Licence
Inherited from the base model: openrail++. This carries the OpenRAIL use-based restrictions
(Attachment A), which bind you as a downstream user of this conversion exactly as they do for the
base model. Read the base model's licence before use or redistribution.