Instructions to use waltgrace/yolo11-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use waltgrace/yolo11-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir yolo11-mlx waltgrace/yolo11-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
yolo11-mlx: YOLO11 on Apple MLX
Pre-converted weights for running YOLO11 detection models on Apple Silicon via MLX Metal GPU.
OmniParser (UI Element Detection)
Microsoft's OmniParser v2 — YOLO11m fine-tuned on 67K web screenshots for detecting interactive UI elements (buttons, links, inputs, icons).
| File | Size | Description |
|---|---|---|
| omniparser_mlx.npz | 80.6 MB | MLX weights (float32) |
| omniparser_mlx.json | metadata | nc=1, class="icon" |
Usage
Performance
~110ms inference on M4 (vs ~400ms ultralytics CPU).