Update app.py

app.py

@@ -14,10 +14,10 @@ vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
 
 speaker_embeddings = {
     "BDL": "spkemb/triniFemale.npy",
-    "CLB": "spkemb/triniFemale.npy",
-    "KSP": "spkemb/triniFemale.npy",
-    "RMS": "spkemb/triniFemale.npy",
-    "SLT": "spkemb/triniFemale.npy",
+    #"CLB": "spkemb/triniFemale.npy",
+    #"KSP": "spkemb/triniFemale.npy",
+    #"RMS": "spkemb/triniFemale.npy",
+    #"SLT": "spkemb/triniFemale.npy",
 }
 
 
@@ -53,7 +53,7 @@ def predict(text, speaker):
     speaker_embedding = torch.tensor(speaker_embedding) #the saved model is already unsqueezed, but is not a tensor, so make it one
     speech = model.generate_speech(input_ids, speaker_embedding, vocoder=vocoder)
 
-    speech = (speech.numpy() * 32767).astype(np.int16)
+    #speech = (speech.numpy() * 32767).astype(np.int16)
     return (16000, speech)
 
 
@@ -98,14 +98,14 @@ article = """
 </div>
 """
 
-examples = [
-    ["It is not in the stars to hold our destiny but in ourselves.", "BDL (male)"],
-    ["The octopus and Oliver went to the opera in October.", "CLB (female)"],
-    ["She sells seashells by the seashore. I saw a kitten eating chicken in the kitchen.", "RMS (male)"],
-    ["Brisk brave brigadiers brandished broad bright blades, blunderbusses, and bludgeons—balancing them badly.", "SLT (female)"],
-    ["A synonym for cinnamon is a cinnamon synonym.", "BDL (male)"],
-    ["How much wood would a woodchuck chuck if a woodchuck could chuck wood? He would chuck, he would, as much as he could, and chuck as much wood as a woodchuck would if a woodchuck could chuck wood.", "CLB (female)"],
-]
+#examples = [ \
+    #["It is not in the stars to hold our destiny but in ourselves.", "BDL (male)"],
+    #["The octopus and Oliver went to the opera in October.", "CLB (female)"],
+    #["She sells seashells by the seashore. I saw a kitten eating chicken in the kitchen.", "RMS (male)"],
+    #["Brisk brave brigadiers brandished broad bright blades, blunderbusses, and bludgeons—balancing them badly.", "SLT (female)"],
+    #["A synonym for cinnamon is a cinnamon synonym.", "BDL (male)"],
+    #["How much wood would a woodchuck chuck if a woodchuck could chuck wood? He would chuck, he would, as much as he could, and chuck as much wood as a woodchuck would if a woodchuck could chuck wood.", "CLB (female)"],
+#]
 
 gr.Interface(
     fn=predict,
@@ -127,5 +127,5 @@ gr.Interface(
     title=title,
     description=description,
     article=article,
-    examples=examples,
+   # examples=examples,
 ).launch()