| ## Models | |
| Welcome to the Ultralytics Models directory! Here you will find a wide variety of pre-configured model configuration | |
| files (`*.yaml`s) that can be used to create custom YOLO models. The models in this directory have been expertly crafted | |
| and fine-tuned by the Ultralytics team to provide the best performance for a wide range of object detection and image | |
| segmentation tasks. | |
| These model configurations cover a wide range of scenarios, from simple object detection to more complex tasks like | |
| instance segmentation and object tracking. They are also designed to run efficiently on a variety of hardware platforms, | |
| from CPUs to GPUs. Whether you are a seasoned machine learning practitioner or just getting started with YOLO, this | |
| directory provides a great starting point for your custom model development needs. | |
| To get started, simply browse through the models in this directory and find one that best suits your needs. Once you've | |
| selected a model, you can use the provided `*.yaml` file to train and deploy your custom YOLO model with ease. See full | |
| details at the Ultralytics [Docs](https://docs.ultralytics.com/models), and if you need help or have any questions, feel free | |
| to reach out to the Ultralytics team for support. So, don't wait, start creating your custom YOLO model now! | |
| ### Usage | |
| Model `*.yaml` files may be used directly in the Command Line Interface (CLI) with a `yolo` command: | |
| ```bash | |
| yolo task=detect mode=train model=yolov8n.yaml data=coco128.yaml epochs=100 | |
| ``` | |
| They may also be used directly in a Python environment, and accepts the same | |
| [arguments](https://docs.ultralytics.com/usage/cfg/) as in the CLI example above: | |
| ```python | |
| from ultralytics import YOLO | |
| model = YOLO("model.yaml") # build a YOLOv8n model from scratch | |
| # YOLO("model.pt") use pre-trained model if available | |
| model.info() # display model information | |
| model.train(data="coco128.yaml", epochs=100) # train the model | |
| ``` | |
| ## Pre-trained Model Architectures | |
| Ultralytics supports many model architectures. Visit https://docs.ultralytics.com/models to view detailed information | |
| and usage. Any of these models can be used by loading their configs or pretrained checkpoints if available. | |
| ## Contributing New Models | |
| If you've developed a new model architecture or have improvements for existing models that you'd like to contribute to the Ultralytics community, please submit your contribution in a new Pull Request. For more details, visit our [Contributing Guide](https://docs.ultralytics.com/help/contributing). | |