Instructions to use kadirnar/Yolov10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- YOLOv10
How to use kadirnar/Yolov10 with YOLOv10:
from ultralytics import YOLOvv10 model = YOLOvv10.from_pretrained("kadirnar/Yolov10") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Leverage PyTorchModelHubMixin
#1
by nielsr - opened
Hi @kadirnar ,
Thanks so much for uploading YOLOv10 checkpoints to make them easier discoverable. :)
Small note though, we prefer to have each model checkpoint uploaded to a separate repository. With the mixin class, it allows to add from_pretrained and push_to_hub capabilities to each model, download stats, automatic model card, etc.
See the docs here: https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin
Opened a PR here: https://github.com/THU-MIG/yolov10/pull/168