Update README.md

README.md

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 ---
 license: apache-2.0
+tags:
+- agriculture
+- plant-disease-detection
+- computer-vision
+- efficientnet
+- mali
 ---
+
+# AgriMali-EfficientNetV2
+
+AgriMali is an AI-powered agricultural assistant designed to help farmers in Mali 🇲🇱 by providing instant diagnosis for plant diseases.
+
+## Overview
+This model is based on the **EfficientNetV2-S** architecture. It has been fine-tuned to classify plant diseases with high accuracy, ensuring robustness and efficiency for mobile-based field applications.
+
+## Performance Metrics
+The model has been validated on a high-quality dataset, achieving the following results:
+
+| Metric | Value |
+| :--- | :--- |
+| **Validation Accuracy** | **98.48%** |
+| **Macro F1-Score** | 97.99% |
+| **Macro AUC** | 99.98% |
+
+## How to use
+You can easily load this model in your Python application using the `huggingface_hub` library:
+
+```python
+from huggingface_hub import hf_hub_download
+import torch
+
+# Download the model weights
+model_path = hf_hub_download(repo_id="Abouba1810/AgriMali-EfficientNetV2", filename="agrimali_best.pth")
+
+# Initialize the model architecture (AgriMaliNet)
+model = AgriMaliNet(num_classes=38) 
+
+# Load the weights
+model.load_state_dict(torch.load(model_path, map_location='cpu'))
+model.eval()