Update app.py

app.py

@@ -1,6 +1,7 @@
 import os
 os.system("pip install gradio==2.8.0b")
 import gradio as gr
+import numpy as np
 
 title = "XM_Tranformer"
 
@@ -8,11 +9,11 @@ description = "Gradio Demo for fairseq S2T: Fast Speech-to-Text Modeling with fa
 
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2010.05171' target='_blank'>fairseq S2T: Fast Speech-to-Text Modeling with fairseq</a> | <a href='https://github.com/pytorch/fairseq/tree/main/examples/speech_to_text' target='_blank'>Github Repo</a></p>"
 
-#examples = [
- #   ["common_voice_es_en.flac","xm_transformer_600m-es_en-multi_domain"],
-  #  ["common_voice_ru_18945535.flac","xm_transformer_600m-ru_en-multi_domain"],
-  #  ["common_voice_fr_19731305.mp3","xm_transformer_600m-fr_en-multi_domain"]
-#]
+examples = [
+  ["common_voice_es_en.flac","xm_transformer_600m-es_en-multi_domain"],
+  ["common_voice_ru_18945535.flac","xm_transformer_600m-ru_en-multi_domain"],
+  ["common_voice_fr_19731305.mp3","xm_transformer_600m-fr_en-multi_domain"]
+]
 
 io1 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-es_en-multi_domain")
 
@@ -33,6 +34,7 @@ io8 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_tr-multi_do
 
     
 def inference(text,model):
+   outtext = np.empty()
    if model == "xm_transformer_600m-es_en-multi_domain":
         outtext = io1(text)
    elif model == "xm_transformer_600m-ru_en-multi_domain":
@@ -59,4 +61,5 @@ gr.Interface(
     gr.outputs.Audio(label="Output"),
     article=article,
     title=title,
+    examples=examples,
     description=description).launch(enable_queue=True)