Update app.py

app.py

@@ -126,13 +126,18 @@ with gr.Blocks(css=css) as block:
     )
     gr.HTML(
         f"""
-       <p><a href="https://github.com/huggingface/parler-tts">Parler-TTS</a> is a training and inference library for
-high-fidelity text-to-speech (TTS) models.</p> 
-<p>The model demonstrated here, German Parler-TTS <a href="https://huggingface.co/davidmeikle/german_parler_tts_mini_v0.1">Mini v0.1 German</a>, 
-has been fine-tuned on a German dataset. It generates high-quality speech with features that can be controlled using a simple text prompt (e.g. gender, background noise, speaking rate, pitch and reverberation). 
-Due to limitations on the dataset, this model might underperform for female voices (we recommend using male voices only).</p>
-<p>By default, Parler-TTS generates 🎲 random male voice characteristics. To ensure 🎯 <b>speaker consistency</b> across generations, try to use consistent descriptions in your prompts.</p>
-<p><b>Important note:</b> this model does NOT work in english, it will generate incoherent audios. But you can still use the original Parler TTS model for that. </p>
+        <p>This model is a version of <strong><a href="https://github.com/huggingface/parler-tts">Parler-TTS</a> Mini V1</strong> trained for the German language.</p>
+        <p>The model has five voices to choose from:</p>
+        <ul>
+          <li>Brenda</li>
+          <li>Hans</li>
+          <li>Christof</li>
+          <li>Ana</li>
+          <li>Elena</li>
+        </ul>
+        <p>Due to limitations on the volume of recordings in the dataset, this model may underperform for female voices at present.</p>
+        <p>By default, Parler-TTS generates random voice characteristics. To ensure speaker consistency across generations, aim to use consistent descriptions in your prompts.</p>
+        <p><b>Please Note:</b> this model has not been trained to work in English, it will generate incoherent output. </p>
         """
     )
     with gr.Row():