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
| { | |
| "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" | |
| } | |