Update README.md

README.md

@@ -13,6 +13,8 @@ These models are part of the paper
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6798c936ece6b7910c55d1e5/3rueSUVk9bOqsFy4fsD-7.png)
 Figure 1. Methodology used in the paper.
 
+## ⚙️ A DEMO on how to apply the trained ML models in Google Colab [with data and model downloads]: [Try it out here](https://colab.research.google.com/drive/1z2uoZtrSv1PPtM6DZaFCN_TR5o8uEwaV?usp=sharing).
+
 ## ⚙️ Model Details
 ### Model Description
 
@@ -32,7 +34,7 @@ Using ML, particularly RFR and XGB, the study demonstrates that SAR-based VIs ca
 Paluba et al. 2025: Estimating vegetation indices and biophysical parameters for Central European temperate forests with Sentinel-1 SAR data and machine learning. Published in Big Earth Data.
 
 **Demo:**
-  Will be provided soon.
+A DEMO on how to apply the trained ML models in Google Colab [with data and model downloads]: [Try it out here](https://colab.research.google.com/drive/1z2uoZtrSv1PPtM6DZaFCN_TR5o8uEwaV?usp=sharing).
 
 ## 🛠 How to Get Started with the Model