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:
- 2f2eacd6d99280189f8945bbd254602221ace7510962561e8133492b58fe3d07
- Size of remote file:
- 2.04 MB
- SHA256:
- 588dbce2b64f71236db8ebc109d5aa50f411f900997e2b0704b0cbca0a0bd180
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