YOLOv8-16bit/README.md

[![Ultralytics CI](https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml/badge.svg)](https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml)

### Install

```bash
pip install ultralytics
```

Development

```
git clone https://github.com/ultralytics/ultralytics
cd ultralytics
pip install -e .
```

## Usage

### 1. CLI

To simply use the latest Ultralytics YOLO models

```bash
yolo task=detect    mode=train    model=yolov8n.yaml      args=...
          classify       predict        yolov8n-cls.yaml  args=...
          segment        val            yolov8n-seg.yaml  args=...
                         export         yolov8n.pt        format=onnx
```

### 2. Python SDK

To use pythonic interface of Ultralytics YOLO model

```python
from ultralytics import YOLO

model = YOLO("yolov8n.yaml")  # create a new model from scratch
model = YOLO(
    "yolov8n.pt"
)  # load a pretrained model (recommended for best training results)
results = model.train(data="coco128.yaml", epochs=100, imgsz=640, ...)
results = model.val()
results = model.predict(source="bus.jpg")
success = model.export(format="onnx")
```

If you're looking to modify YOLO for R&D or to build on top of it, refer to [Using Trainer](<>) Guide on our docs.