Instructions to use webAI-Official/yolo26n-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use webAI-Official/yolo26n-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir yolo26n-mlx webAI-Official/yolo26n-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Sync README with template generator (cosmetic, identical render)
Browse files
README.md
CHANGED
|
@@ -33,8 +33,7 @@ Pure-MLX weights for **YOLO26n**, ready to run on Apple Silicon with
|
|
| 33 |
[`yolo-mlx`](https://github.com/thewebAI/yolo-mlx). No PyTorch at runtime,
|
| 34 |
no cloud calls, no waiting on someone else's API — everything stays on your Mac.
|
| 35 |
|
| 36 |
-
This is the smallest variant in the YOLO26 MLX family: ideal for real-time
|
| 37 |
-
webcam apps, low-latency demos, and anything where every millisecond counts.
|
| 38 |
|
| 39 |
## Quickstart
|
| 40 |
|
|
|
|
| 33 |
[`yolo-mlx`](https://github.com/thewebAI/yolo-mlx). No PyTorch at runtime,
|
| 34 |
no cloud calls, no waiting on someone else's API — everything stays on your Mac.
|
| 35 |
|
| 36 |
+
This is the smallest variant in the YOLO26 MLX family: ideal for real-time webcam apps, low-latency demos, and anything where every millisecond counts.
|
|
|
|
| 37 |
|
| 38 |
## Quickstart
|
| 39 |
|