---
license: agpl-3.0
pipeline_tag: object-detection
tags:
- ultralytics
- yolo
- yolov8
- pytorch_model_hub_mixin
- model_hub_mixin
---

This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration.

## Installation

First install the package:

```bash
!pip install -q git+https://github.com/nielsrogge/ultralytics.git@feature/add_hf
```

## Usage

YOLOv8 may also be used directly in a Python environment, and accepts the same [arguments](https://docs.ultralytics.com/usage/cfg/) as in the CLI:

```python
from ultralytics import YOLO

# Load a model
model = YOLO.from_pretrained("nielsr/yolov8n")

# Use the model
model.train(data="coco128.yaml", epochs=3)  # train the model
metrics = model.val()  # evaluate model performance on the validation set
results = model("https://ultralytics.com/images/bus.jpg")  # predict on an image
path = model.export(format="onnx")  # export the model to ONNX format
```

See YOLOv8 [Python Docs](https://docs.ultralytics.com/usage/python) for more examples.