| description: Explore the base class for implementing YOLO models with unified APIs for training, validation, prediction, and more. Learn how to utilize different task types and model configurations. | |
| keywords: YOLO model, Ultralytics, machine learning, deep learning, PyTorch model, training, validation, prediction, exporting, benchmarking, Ultralytics HUB, Triton Server | |
| # Reference for `ultralytics/engine/model.py` | |
| !!! Note | |
| This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/engine/model.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/engine/model.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/engine/model.py) 🛠️. Thank you 🙏! | |
| <br> | |
| ## ::: ultralytics.engine.model.Model | |
| <br><br> | |