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:
- e94dba89c1e0f3cf0b2e88ee0a9be1e0735e408a1f9b119caf4f320d469278f2
- Size of remote file:
- 108 kB
- SHA256:
- a9f038e54f368d0058a8dbe41062eac52e4912af19400c594af4e3be0e028fef
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