Core ML Model Zoo
Collection
PyTorch models converted to Core ML for on-device inference on iPhone, iPad and Mac. • 46 items • Updated • 1
Stable Audio Open — Core ML
Text-to-Music, 2024
Text-to-music. Up to 11.9s stereo 44.1 kHz. Rectified flow DiT + T5 + Oobleck VAE.
Core ML conversion of stabilityai/stable-audio-open-small for on-device inference on iPhone, iPad and Mac. Converted with coremltools; the packages are stateless, so all sequencing and buffering lives in your Swift code.
| Task | text to audio |
| Upstream | stabilityai/stable-audio-open-small |
| Packages | 4 |
| Download size | 1.41 GB |
| Minimum iOS | 17.0 |
| Peak RAM | ~1200 MB |
Files
| File | Size | Compute units | SHA-256 |
|---|---|---|---|
StableAudioT5Encoder.mlpackage.zip |
94 MB | cpuAndGPU |
319a8ba775d30924… |
StableAudioNumberEmbedder.mlpackage.zip |
367 KB | cpuAndGPU |
04bdc5de00a2cf1c… |
StableAudioDiT.mlpackage.zip |
1.18 GB | cpuOnly |
b17da4fc4df85782… |
StableAudioVAEDecoder.mlpackage.zip |
138 MB | cpuAndGPU |
7207544cca9799cc… |
t5_vocab.json |
732 KB | - |
7c9ff3ac1b3dbcaa… |
| Total | 1.41 GB |
compute_units is not a suggestion -- it is the configuration the conversion was verified against. Moving a package to a different compute unit can silently change the numerics (FP16 attention overflow) or crash on the GPU.
Download
hf download mlboydaisuke/coreml-zoo --include "stableaudio/*" --local-dir ./stable_audio
unzip './stable_audio/stableaudio/*.zip' -d ./stable_audio
Use in Swift
import CoreML
let config = MLModelConfiguration()
config.computeUnits = .cpuAndGPU // as converted — see the table above
// Unzip the .mlpackage, drop it into your Xcode target and Xcode compiles it
// at build time:
let model = try StableAudioT5Encoder(configuration: config)
// ...or compile a downloaded .mlpackage at runtime:
let compiled = try await MLModel.compileModel(at: mlpackageURL)
let model = try MLModel(contentsOf: compiled, configuration: config)
This model is split into 4 Core ML packages that are driven in sequence from Swift. Load them one at a time, copy the outputs out of the
MLMultiArraybuffers and release each model before loading the next — two large Core ML models resident at once will OOM on an iPhone.
Demo
- Sample app —
sample_apps/StableAudioDemo, a standalone SwiftUI project. - Models Zoo — this model is downloadable and runnable inside the Models Zoo app on the App Store, no build required.
Conversion
- Script:
convert_stable_audio.py - Pitfalls hit during conversion (FP16 overflow, ANE buffer limits, stride handling):
docs/coreml_conversion_notes.md - Model index: CoreML-Models
License
The conversion inherits the upstream license: Stability AI Community License. See https://huggingface.co/stabilityai/stable-audio-open-small.
Free for non-commercial and limited commercial use; see the Stability AI Community License.
Credits
- Upstream authors: stabilityai/stable-audio-open-small, 2024
- Core ML conversion: john-rocky (Daisuke Majima)
More models in this format: Core ML Model Zoo — 46 models, each with the recipe that produced it.
Want a different model on-device? Open a request — free, open weights only; the export and its measured numbers get published publicly.
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Model tree for mlboydaisuke/Stable-Audio-Open-Small-CoreML
Base model
stabilityai/stable-audio-open-small