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
File size: 329 Bytes
2657d76 12f0910 2657d76 12f0910 2657d76 12f0910 2657d76 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"architectures": [
"UNetForSegmentation"
],
"batch_size": 8,
"downsample_factor": 1.0,
"dtype": "float32",
"img_size": 128,
"k": 5,
"model_arch": "unet",
"model_type": "segmentation",
"n_filts": 128,
"norm": null,
"num_channels": 3,
"num_classes": 4,
"t": 3,
"transformers_version": "5.3.0"
}
|