diff --git a/bert_vits2/attentions.py b/bert_vits2/attentions.py
index 80df44f..a027094 100644
--- a/bert_vits2/attentions.py
+++ b/bert_vits2/attentions.py
@@ -42,11 +42,11 @@ def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_s
         self.kernel_size = kernel_size
         self.p_dropout = p_dropout
         self.window_size = window_size
-        if isflow:
-            cond_layer = torch.nn.Conv1d(256, 2 * hidden_channels * n_layers, 1)
-            self.cond_pre = torch.nn.Conv1d(hidden_channels, 2 * hidden_channels, 1)
-            self.cond_layer = weight_norm(cond_layer, name='weight')
-            self.gin_channels = 256
+        # if isflow:
+        #     cond_layer = torch.nn.Conv1d(256, 2 * hidden_channels * n_layers, 1)
+        #     self.cond_pre = torch.nn.Conv1d(hidden_channels, 2 * hidden_channels, 1)
+        #     self.cond_layer = weight_norm(cond_layer, name='weight')
+        #     self.gin_channels = 256
         self.cond_layer_idx = self.n_layers
         if 'gin_channels' in kwargs:
             self.gin_channels = kwargs['gin_channels']
diff --git a/bert_vits2/models.py b/bert_vits2/models.py
index e4d04da..ce25763 100644
--- a/bert_vits2/models.py
+++ b/bert_vits2/models.py
@@ -643,8 +643,8 @@ def __init__(self,
         self.sdp = StochasticDurationPredictor(hidden_channels, 192, 3, 0.5, 4, gin_channels=gin_channels)
         self.dp = DurationPredictor(hidden_channels, 256, 3, 0.5, gin_channels=gin_channels)
 
-        if n_speakers >= 1:
-            self.emb_g = nn.Embedding(n_speakers, gin_channels)
+        if self.n_speakers > 0:
+            self.emb_g = nn.Embedding(self.n_speakers, gin_channels)
         else:
             self.ref_enc = ReferenceEncoder(spec_channels, gin_channels)