Update README.md

README.md

@@ -12,7 +12,7 @@ The model was trained using bands RGB (2, 3 and 4) (Red, Green and Blue) of the
 The input shape of the model is 224, 224, 3. To extract features you should remove the last layer.
 
 The model can be read as (example in jupyer):
-"""
+```
 !git lfs install
 !git clone https://huggingface.co/MITCriticalData/Sentinel-2_ViT_Autoencoder_RGB_full_Colombia_Dataset
     
@@ -21,7 +21,19 @@ from transformers import TFViTModel
 
 
 model = tf.keras.models.load_model('Sentinel-2_ViT_Autoencoder_RGB_full_Colombia_Dataset', custom_objects={"TFViTModel": TFViTModel})
-"""
+```
+
+You can extract the embeddings removing the last layer using:
+```
+import tensorflow as tf
+
+model = tf.keras.Sequential()
+
+for layer in autoencoder.layers[:-1]: # just exclude last layer from copying
+    model.add(layer)    
+        
+```
+
 
 ## Intended uses & limitations