Update README.md

README.md

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-license: mit
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+# Histopathologic Cancer Detection - EfficientNetV2S & ViT-Hybrid
+This repository contains models for detecting metastatic cancer in histopathologic images.
+- **EfficientNetV2S**: A Baseline CNN-based model for local feature extraction.
+- **ViT-Hybrid**: A Transformer-based model that learns global dependencies.
+Both models were trained on the [Histopathologic Cancer Detection Kaggle dataset](https://www.kaggle.com/competitions/histopathologic-cancer-detection/data)
+
+## Model Performance
+- **EfficientNetV2S**
+  - Accuracy: 93.59% (Private), 93.74% (Public)
+  - AUC: 0.9774
+- **ViT-Hybrid**
+  - Accuracy: 95.07% (Private), 94.87% (Public)
+  - AUC: 0.9791
+- **ViT-Hybrid + TTA (Test-Time Augmentation)**
+  - Accuracy: 96.50% (Private), 96.75% (Public)
+
+## Model Use
+from huggingface_hub import hf_hub_download
+from tensorflow.keras.models import load_model
+
+# Download EfficientNetV2S model
+model_path = hf_hub_download(repo_id="MooseML/EfficientNet-Cancer-Detection", filename="efficientnet_cancer_model.h5")
+model = load_model(model_path)
+
+# Download ViT-Hybrid model
+model_path_vit = hf_hub_download(repo_id="MooseML/EfficientNet-Cancer-Detection", filename="ViT_hybrid_cancer_model.h5")
+model_vit = load_model(model_path_vit)
+
+## Github and Kaggle Links for Full Training Pipeline
+- Full Training Code: [GitHub Repository](https://github.com/MooseML/Histopathologic-Cancer-Detection)
+- Kaggle Competition: [Histopathologic Cancer Detection](https://www.kaggle.com/competitions/histopathologic-cancer-detection)
+
+
+---
+license: mit
+---