Instructions to use GleghornLab/lymph_node_segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GleghornLab/lymph_node_segmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="GleghornLab/lymph_node_segmentation")# Load model directly from transformers import UNetForSegmentation model = UNetForSegmentation.from_pretrained("GleghornLab/lymph_node_segmentation", dtype="auto") - Notebooks
- Google Colab
- Kaggle
set norm to True - I don't know why it didn't load from wandb correctly
Browse files- config.json +1 -1
config.json
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@@ -10,7 +10,7 @@
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"model_arch": "unet",
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"model_type": "segmentation",
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"n_filts": 128,
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"norm":
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"num_channels": 3,
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"num_classes": 4,
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"t": 3,
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"model_arch": "unet",
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"model_type": "segmentation",
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"n_filts": 128,
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"norm": true,
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"num_channels": 3,
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"num_classes": 4,
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"t": 3,
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