Update app.py

app.py

@@ -7,7 +7,7 @@ import torchaudio
 import gradio as gr
 import re
 
-llasa_model_id = 'OmniAICreator/Llasa-1B-run1'
+llasa_model_id = 'OmniAICreator/Galgame-Llasa-1B'
 
 tokenizer = AutoTokenizer.from_pretrained(llasa_model_id)
 
@@ -112,7 +112,7 @@ def extract_speech_ids(speech_tokens_str):
     return speech_ids
 
 @spaces.GPU(duration=60)
-def infer(sample_audio_path, target_text, temperature, top_p,  progress=gr.Progress()):
+def infer(sample_audio_path, target_text, temperature, top_p, repetition_penalty, progress=gr.Progress()):
     if not target_text or not target_text.strip():
         gr.Warning("Please input text to generate audio.")
         return None, None
@@ -183,7 +183,8 @@ def infer(sample_audio_path, target_text, temperature, top_p,  progress=gr.Progr
             eos_token_id=speech_end_id,
             do_sample=True,
             top_p=top_p,
-            temperature=temperature
+            temperature=temperature,
+            repetition_penalty=repetition_penalty,
         )
 
         # Extract the speech tokens
@@ -222,6 +223,7 @@ with gr.Blocks() as app_tts:
     with gr.Row():
         temperature_slider = gr.Slider(minimum=0.0, maximum=1.0, value=0.8, step=0.05, label="Temperature")
         top_p_slider = gr.Slider(minimum=0.0, maximum=1.0, value=1.0, step=0.05, label="Top-p")
+        repetition_penalty_slider = gr.Slider(minimum=1.0, maximum=1.5, value=1.1, step=0.05, label="Repetition Penalty")
 
     generate_btn = gr.Button("Synthesize", variant="primary")
 
@@ -234,6 +236,7 @@ with gr.Blocks() as app_tts:
             gen_text_input,
             temperature_slider,
             top_p_slider,
+            repetition_penalty_slider,
         ],
         outputs=[audio_output],
     )