Instructions to use aholk/LN_segmentation_sweep_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aholk/LN_segmentation_sweep_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="aholk/LN_segmentation_sweep_v2")# Load model directly from transformers import UNetForSegmentation model = UNetForSegmentation.from_pretrained("aholk/LN_segmentation_sweep_v2", dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 702e51c6321f6f490dc487964827d340c6ec2696fb8a930d151bb040ad08480b
- Size of remote file:
- 194 kB
- SHA256:
- 40f81873fdf5e1821f8a7b5f5a9351946142fed503b28b5a6635816cf5235141
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