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:
- b64a67be3c31a6839a8ba15585822dd7ab44c8e345918c8234651ef8f966d1a3
- Size of remote file:
- 181 kB
- SHA256:
- f40ec01998d05597aea4ca673313f9e9a443b13a3a699616fbf3429859bf5656
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