Instructions to use mlboydaisuke/YOLO26s-CoreML with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use mlboydaisuke/YOLO26s-CoreML with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("mlboydaisuke/YOLO26s-CoreML") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
File size: 2,799 Bytes
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license: agpl-3.0
library_name: coreml
pipeline_tag: object-detection
tags:
- coreml
- core-ml
- ios
- macos
- apple
- on-device
- yolo
- ultralytics
- real-time
---
# YOLO26s — Core ML
*NMS-Free Detection, 2026*
NMS-free object detection. 640×640 input, 80 COCO classes.
<p><img src="https://huggingface.co/mlboydaisuke/YOLO26s-CoreML/resolve/main/media/bc27d62111.png" alt="YOLO26s demo"></p>
Core ML conversion of [ultralytics/ultralytics](https://github.com/ultralytics/ultralytics) 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 | object detection |
| Upstream | [ultralytics/ultralytics](https://github.com/ultralytics/ultralytics) |
| Packages | 1 |
| Download size | 17 MB |
| Minimum iOS | 17.0 |
| Peak RAM | ~300 MB |
## Files
| File | Size | Compute units | SHA-256 |
|---|---:|---|---|
| `yolo26s.mlpackage.zip` | 17 MB | `all` | `0ec02fb0cf2dbd6e…` |
| **Total** | **17 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 "yolo26/*" --local-dir ./yolo26s
unzip './yolo26s/yolo26/*.zip' -d ./yolo26s
```
## Use in Swift
```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 yolo26s(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)
```
## Demo
- **Sample app** — [`sample_apps/YOLO26Demo`](https://github.com/john-rocky/CoreML-Models/tree/master/sample_apps/YOLO26Demo), a standalone SwiftUI project.
- **Models Zoo** — this model is downloadable and runnable inside the [Models Zoo app](https://apps.apple.com/app/id6762083207) on the App Store, no build required.
## Conversion
- Pitfalls hit during conversion (FP16 overflow, ANE buffer limits, stride handling): [`docs/coreml_conversion_notes.md`](https://github.com/john-rocky/CoreML-Models/blob/master/docs/coreml_conversion_notes.md)
- Model index: [CoreML-Models](https://github.com/john-rocky/CoreML-Models)
## License
The conversion inherits the upstream license: **AGPL-3.0**.
## Credits
- Upstream authors: [ultralytics/ultralytics](https://github.com/ultralytics/ultralytics), 2026
- Core ML conversion: john-rocky (Daisuke Majima)
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