diff --git a/config.json b/config.json
index 9c4b2271..bf2ad383 100644
--- a/config.json
+++ b/config.json
@@ -136,7 +136,7 @@
         "gst_style_input": null,        // Condition the style input either on a 
                                         // -> wave file [path to wave] or 
                                         // -> dictionary using the style tokens {'token1': 'value', 'token2': 'value'} example {"0": 0.15, "1": 0.15, "5": -0.15}  
-                                        // with the dictionary being len(dict) == len(gst_style_tokens).
+                                        // with the dictionary being len(dict) <= len(gst_style_tokens).
         "gst_embedding_dim": 512,       
         "gst_num_heads": 4,
         "gst_style_tokens": 10
diff --git a/models/tacotron_abstract.py b/models/tacotron_abstract.py
index b7d9faf2..c868a18a 100644
--- a/models/tacotron_abstract.py
+++ b/models/tacotron_abstract.py
@@ -175,13 +175,7 @@ class TacotronAbstract(ABC, nn.Module):
                 gst_outputs_att = self.gst_layer.style_token_layer.attention(query, key)
                 gst_outputs = gst_outputs + gst_outputs_att * v_amplifier
         elif style_input is None:
-            query = torch.zeros(1, 1, self.gst_embedding_dim//2).to(device)
-            _GST = torch.tanh(self.gst_layer.style_token_layer.style_tokens)
             gst_outputs = torch.zeros(1, 1, self.gst_embedding_dim).to(device)
-            for k_token in range(self.gst_style_tokens):
-                key = _GST[int(k_token)].unsqueeze(0).expand(1, -1, -1)
-                gst_outputs_att = self.gst_layer.style_token_layer.attention(query, key)
-                gst_outputs = gst_outputs + gst_outputs_att * 0
         else:
             gst_outputs = self.gst_layer(style_input)
         embedded_gst = gst_outputs.repeat(1, inputs.size(1), 1)