Update README.md

README.md

@@ -1,6 +1,6 @@
 # 📡 **LWM: Large Wireless Model**
 
-**[🚀 Click here to try the Interactive Demo!](https://huggingface.co/spaces/sadjadalikhani/lwm-interactive-demo)**
+**[🚀 Click here to try the Interactive Demo!](https://huggingface.co/spaces/wi-lab/lwm-interactive-demo)**
 
 Welcome to **LWM** (Large Wireless Model) — a pre-trained model designed for processing and feature extraction from wireless communication datasets, particularly the **DeepMIMO** dataset. This guide provides step-by-step instructions to set up your environment, install the required packages, clone the repository, load data, and perform inference using LWM.
 
@@ -111,7 +111,7 @@ Now, clone the **LWM** model repository to your local system.
 
 ```bash
 # Step 1: Clone the model repository (if not already cloned)
-model_repo_url = "https://huggingface.co/sadjadalikhani/lwm"
+model_repo_url = "https://huggingface.co/wi-lab/lwm"
 model_repo_dir = "./LWM"
 
 if not os.path.exists(model_repo_dir):
@@ -138,7 +138,7 @@ You can now clone specific scenarios from the DeepMIMO dataset, as detailed in t
 
 #### **Clone the Scenarios:**
 ```python
-dataset_repo_url = "https://huggingface.co/datasets/sadjadalikhani/lwm"  # Base URL for dataset repo
+dataset_repo_url = "https://huggingface.co/datasets/wi-lab/lwm"  # Base URL for dataset repo
 scenario_names = np.array([
     "city_18_denver", "city_15_indianapolis", "city_19_oklahoma", 
     "city_12_fortworth", "city_11_santaclara", "city_7_sandiego"
@@ -220,7 +220,7 @@ By selecting either `cls_emb` or `channel_emb`, you leverage the pre-trained mod
 
 To experience **LWM** interactively, visit our demo hosted on Hugging Face Spaces:
 
-[**Try the Interactive Demo!**](https://huggingface.co/spaces/sadjadalikhani/LWM-Interactive-Demo)
+[**Try the Interactive Demo!**](https://huggingface.co/spaces/wi-lab/lwm-interactive-demo)
 
 ---