Instructions to use riversnow/so101-segmentation-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use riversnow/so101-segmentation-model with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("riversnow/so101-segmentation-model", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download image.png from riversnow/so101-segmentation-model: direct link, hf CLI and curl.
- Browser
- Download file 903 kB
-
https://huggingface.co/riversnow/so101-segmentation-model/resolve/main/image.png
- Command line
-
hf download hf://riversnow/so101-segmentation-model/image.png
-
curl -L -o image.png https://huggingface.co/riversnow/so101-segmentation-model/resolve/main/image.png
903 kB

- Xet hash:
- a02e60d732e4b68dfb1bfef01fbfbbc1ec12ff76d1a4d9b5e36aca621cb6b96f
- Size of remote file:
- 903 kB
- SHA256:
- 5625ffd4fee8efcc004e32c202593faee5deeb15efd6d59f304fe73a283c1642
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