Update README.md

README.md

@@ -15,23 +15,23 @@ The input shape of the model is 224, 224, 12. To extract features you should rem
 The model can be read as (example in jupyer):
 ```
 !git lfs install
-!git clone https://huggingface.co/MITCriticalData/Sentinel-2_ViT_Autoencoder_RGB
+!git clone https://huggingface.co/MITCriticalData/Sentinel-2_ViT_Autoencoder_12Bands
     
 import tensorflow as tf
 from transformers import TFViTModel
 
 
-model = tf.keras.models.load_model('Sentinel-2_ViT_Autoencoder_RGB', custom_objects={"TFViTModel": TFViTModel})
+model = tf.keras.models.load_model('Sentinel-2_ViT_Autoencoder_12Bands', custom_objects={"TFViTModel": TFViTModel})
 ```
 
 You can extract the embeddings removing the last layer using:
 ```
 import tensorflow as tf
 
-model = tf.keras.Sequential()
+backbone = tf.keras.Sequential()
 
-for layer in autoencoder.layers[:-1]: # just exclude last layer from copying
-    model.add(layer)    
+for layer in model.layers[:-1]: # just exclude last layer from copying
+    backbone.add(layer)    
         
 ```