Update app.py

app.py

@@ -127,29 +127,18 @@ def ljspeech_example_cacher(text, n_timesteps, mel_temp, length_scale, spk=-1):
 
 
 def main():
-    description = """# AkylAI TTS mini
-    We present to you a fast speech synthesis model in the Kyrgyz language.
-
-    
-    This is a new approach to non-autoregressive neural TTS that uses conditional stream matching (similar to rectified streams) to speed up ODE-based speech synthesis.
-    Method:
-
-    * Is probabilistic
-    * Has compact memory footprint
-    * Sounds highly natural
-    * Is very fast to synthesise from
-   
-    """
+    description = """# AkylAI TTS mini"""
 
     with gr.Blocks(title="AkylAI TTS") as demo:
         processed_text = gr.State(value=None)
         processed_text_len = gr.State(value=None)
 
         with gr.Box():
-
-          with gr.Column():
-              image_url = "https://github.com/simonlobgromov/Matcha-TTS/blob/main/photo_2024-04-07_15-59-52.png?raw=true"
-              gr.Image(image_url, label="Matcha-TTS logo", width=560, height=315)
+            with gr.Row():
+                gr.Markdown(description, scale=3)
+            with gr.Row():
+                image_url = "https://github.com/simonlobgromov/Matcha-TTS/blob/main/photo_2024-04-07_15-59-52.png?raw=true"
+                gr.Image(image_url, label="Matcha-TTS logo", width=560, height=315)
 
         with gr.Box():
             radio_options = list(RADIO_OPTIONS.keys())