Update app.py (#18)

- Update app.py (3105f149349cfc91d97ef64d2787a500019fbdd2)

app.py

@@ -13,7 +13,7 @@ device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
 
 repo_id =  "parler-tts/parler-tts-mini-v1"
-repo_id_large = "ylacombe/parler-large-v1-og"
+repo_id_large = "parler-tts/parler-tts-large-v1"
 
 model = ParlerTTSForConditionalGeneration.from_pretrained(repo_id).to(device)
 model_large = ParlerTTSForConditionalGeneration.from_pretrained(repo_id_large).to(device)
@@ -154,7 +154,7 @@ with gr.Blocks(css=css) as block:
         are trained using 45k hours of narrated English audiobooks. 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).</p>
 
-        <p>By default, Parler-TTS generates 🎲 random voice. To ensure 🎯 <b> speaker consistency </b> across generations, these checkpoints were also trained on 34 speakers, characterized by name (e.g. Jon, Lea, Gary, Jenna, Mike, Laura).</p>
+        <p>By default, Parler-TTS generates 🎲 random voice. To ensure 🎯 <b> speaker consistency </b> across generations, these checkpoints were also trained on 34 speakers, characterized by name (e.g. Jon, Lea, Gary, Jenna, Mike, Laura). Learn more about this <a href="https://github.com/huggingface/parler-tts/blob/main/INFERENCE.md#speaker-consistency"> here </a>.</p>
         
         <p>To take advantage of this, simply adapt your text description to specify which speaker to use: `Jon's voice is monotone...`</p>
         """