Update README.md

README.md

@@ -251,7 +251,18 @@ By selecting either `cls_emb` or `channel_emb`, you leverage the pre-trained mod
 
 ---
 
-### 10. **Explore the Interactive Demo**
+### 10. **Generate Labels if Necessary**
+If your dataset requires labels, you can easily generate them using DeepMIMO data. Here's an example to create labels for either LoS/NLoS classification or beam prediction, depending on the scenario selected:You can generate labels for your dataset using the DeepMIMO data. Below is an example for generating labels for the LoS/NLoS classification and beam prediction tasks based on the dataset scenario you chose earlier:
+```python
+from input_preprocess import create_labels
+tasks = ['LoS/NLoS Prediction', 'Beam Prediction']
+task = tasks[1] # Choose 0 for LoS/NLoS labels or 1 for beam prediction labels.
+labels = create_labels(task, selected_scenario_names, n_beams=64)
+```
+
+---
+
+### 11. **Explore the Interactive Demo**
 
 To experience **LWM** interactively, visit our demo hosted on Hugging Face Spaces: