Update README.md

README.md

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-# ModelAuditor
-This repository contains the pretrained models for ModelAuditor
+# ModelAuditor Pre-trained Models
+
+Pre-trained ResNet50 models for medical image classification, used with the [ModelAuditor](https://github.com/lukaskuhndkfz/ModelAuditor) framework for AI-powered model auditing and robustness evaluation.
+
+## Models
+
+| Model | Domain | Task | Input Size |
+|-------|--------|------|------------|
+| `camelyon17_resnet50_1_224.pt` | Pathology | Tumor detection in lymph node sections | 224x224 |
+| `chexpert_resnet50_1_224.pt` | Radiology | Chest X-ray classification | 224x224 |
+| `ham10000_resnet50_1_224.pt` | Dermatology | Skin lesion classification (melanoma vs. benign keratosis) | 224x224 |
+
+## Usage
+
+### Download Models
+
+```bash
+pip install huggingface_hub
+
+# Download all models
+huggingface-cli download lukaskuhndkfz/ModelAuditor --local-dir models
+
+# Or download individually
+huggingface-cli download lukaskuhndkfz/ModelAuditor ham10000_resnet50_1_224.pt --local-dir models
+
+Use with ModelAuditor
+
+git clone https://github.com/lukaskuhndkfz/ModelAuditor
+cd ModelAuditor
+pip install -e ".[medical]"
+
+# Run auditing
+python main.py --model resnet50 --dataset ham10000 --weights models/ham10000_resnet50_1_224.pt
+
+Load in PyTorch
+
+import torch
+from torchvision.models import resnet50
+
+model = resnet50(num_classes=2)
+model.load_state_dict(torch.load("ham10000_resnet50_1_224.pt", map_location="cpu"))
+model.eval()
+
+Datasets
+
+- Camelyon17: https://wilds.stanford.edu/datasets/#camelyon17
+- CheXpert: https://stanfordmlgroup.github.io/competitions/chexpert/
+- HAM10000: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/DBW86T