Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

GleghornLab
/
lymph_node_segmentation

Image Segmentation
Transformers
Safetensors
PyTorch
segmentation
multilabel
unet
medical-imaging
Model card Files Files and versions
xet
Community

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
lymph_node_segmentation
2.21 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
aholk's picture
aholk
updated to clarify the metrics are from the test scores not the validation scores
e245337 verified about 6 hours ago
  • .gitattributes
    1.52 kB
    initial commit 2 months ago
  • README.md
    2.13 kB
    updated to clarify the metrics are from the test scores not the validation scores about 6 hours ago
  • config.json
    329 Bytes
    Upload folder using huggingface_hub 2 months ago
  • model.safetensors
    2.21 GB
    xet
    Upload folder using huggingface_hub 2 months ago