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mlboydaisuke/
Hyper-SD-1step-CoreML

Name: Hyper-SD-1step-CoreML
Availability: InStock

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Hyper-SD (1-Step) — Core ML

ByteDance, 2024

Single-step text-to-image from SD1.5 via TCD distillation. 512×512. Chunked UNet (6-bit).

Core ML conversion of ByteDance/Hyper-SD 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 image
Upstream	ByteDance/Hyper-SD
Packages	4
Download size	905 MB
Minimum iOS	17.0
Peak RAM	~1000 MB

Files

File	Size	Compute units	SHA-256
`HyperSDTextEncoder.mlpackage.zip`	216 MB	`cpuAndNeuralEngine`	`201b0fcc3573811a…`
`HyperSDUnetChunk1.mlpackage.zip`	310 MB	`cpuAndNeuralEngine`	`279da11b8231aeeb…`
`HyperSDUnetChunk2.mlpackage.zip`	290 MB	`cpuAndNeuralEngine`	`0a700d11a105da58…`
`HyperSDVAEDecoder.mlpackage.zip`	87 MB	`cpuAndGPU`	`1260371542d845a2…`
`vocab.json`	1 MB	`-`	`e089ad92ba36837a…`
`merges.txt`	512 KB	`-`	`9fd691f7c8039210…`
Total	905 MB

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

bash

hf download mlboydaisuke/coreml-zoo --include "hypersd/*" --local-dir ./hypersd
unzip './hypersd/hypersd/*.zip' -d ./hypersd

Use in Swift

swift

import CoreML

let config = MLModelConfiguration()
config.computeUnits = .cpuAndNeuralEngine   // 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 HyperSDTextEncoder(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 MLMultiArray buffers 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/HyperSDDemo, 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_hypersd.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: OpenRAIL-M.

Credits

Upstream authors: ByteDance/Hyper-SD, 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.

mlboydaisuke/Hyper-SD-1step-CoreML