YOLO-World — Core ML
Open-Vocabulary Detection, 2024
Open-vocabulary detection. Type any text query. YOLO-World V2-S + CLIP ViT-B/32.
Core ML conversion of AILab-CVC/YOLO-World 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 | zero shot object detection |
| Upstream | AILab-CVC/YOLO-World |
| Packages | 2 |
| Download size | 134 MB |
| Minimum iOS | 17.0 |
| Peak RAM | ~600 MB |
Files
| File | Size | Compute units | SHA-256 |
|---|---|---|---|
yoloworld_detector.mlpackage.zip | 23 MB | all | 611d299ae74c83f9… |
clip_text_encoder.mlpackage.zip | 111 MB | cpuOnly | 45770a743297e8c2… |
| Total | 134 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
hf download mlboydaisuke/coreml-zoo --include "yoloworld/*" --local-dir ./yoloworld
unzip './yoloworld/yoloworld/*.zip' -d ./yoloworld
Use in Swift
import CoreML
let config = MLModelConfiguration()
config.computeUnits = .all // 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 yoloworld_detector(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 2 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/YOLOWorldDemo, 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
- 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: GPL-3.0.
Credits
- Upstream authors: AILab-CVC/YOLO-World, 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.