Update app.py

app.py

@@ -26,7 +26,7 @@ model = AutoModel(
     trust_remote_code=False,
     remote_code="./model.py",
     vad_model="fsmn-vad",
-    punc_model="ct-punc", 
+    punc_model="iic/speech_campplus_sv_zh-cn_16k-common", 
     vad_kwargs={"max_single_segment_time": 15000},
     ncpu=torch.get_num_threads(),
     batch_size=1,
@@ -34,7 +34,7 @@ model = AutoModel(
     device=device,
 )
 
-def transcribe_audio(file_path, vad_model="fsmn-vad", punc_model="ct-punc", vad_kwargs='{"max_single_segment_time": 15000}', 
+def transcribe_audio(file_path, vad_model="fsmn-vad", punc_model="iic/speech_campplus_sv_zh-cn_16k-common", vad_kwargs='{"max_single_segment_time": 15000}', 
                      batch_size=1, language="auto", use_itn=True, batch_size_s=60, 
                      merge_vad=True, merge_length_s=15, batch_size_threshold_s=50, 
                      hotword=" ", ban_emo_unk=True):
@@ -66,7 +66,7 @@ def transcribe_audio(file_path, vad_model="fsmn-vad", punc_model="ct-punc", vad_
 inputs = [
     gr.Audio(type="filepath"),
     gr.Textbox(value="fsmn-vad", label="VAD Model"),
-    gr.Textbox(value="ct-punc", label="PUNC Model"),
+    gr.Textbox(value="iic/speech_campplus_sv_zh-cn_16k-common", label="PUNC Model"),
     gr.Textbox(value='{"max_single_segment_time": 15000}', label="VAD Kwargs"),
     gr.Slider(1, 10, value=1, step=1, label="Batch Size"),
     gr.Textbox(value="auto", label="Language"),