This model has been pushed to the Hub using the PytorchModelHubMixin integration.
Installation
First install the package:
!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 as in the CLI:
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 for more examples.
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