Create app.py

app.py

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+import torch
+import torchaudio
+import torch.nn as nn
+import torch.nn.functional as F
+
+import IPython
+
+from api import TextToSpeech
+from utils.audio import load_audio, get_voices
+
+# This will download all the models used by Tortoise from the HF hub.
+tts = TextToSpeech()
+
+voices = [
+  "angie",
+  "daniel",
+  "deniro",
+  "emma",
+  "freeman",
+  "geralt",
+  "halle",
+  "jlaw",
+  "lj",
+  "snakes",
+  "tom",
+  "William",
+]
+voices = get_voices()
+
+preset = "fastest"
+
+def inference(text, voice):
+  cond_paths = voices[voice]
+  conds = []
+  for cond_path in cond_paths:
+      c = load_audio(cond_path, 22050)
+      conds.append(c)
+      gen = tts.tts_with_preset(text, conds, preset)
+      return gen
+      
+ text = "Joining two modalities results in a surprising increase in generalization! What would happen if we combined them all?"
+ iface = gr.Interface(
+    generate_tone,
+    inputs=[
+        gr.inputs.Textbox(type="text", default=text, label="Text"),
+        gr.inputs.Dropdown(voices, type="index"),
+    ],
+    outputs="audio",
+)
+
+iface.launch()