Update app.py

app.py

@@ -27,6 +27,8 @@ tokenizer_ner = AutoTokenizer.from_pretrained(model_name)
 model_ner = AutoModelForTokenClassification.from_pretrained(model_name)
 predict_ner = TokenClassificationPipeline(model=model_ner, tokenizer=tokenizer_ner)
 
+examples = sorted(glob(os.path.join(EXAMPLE_DIR, '*.wav')))
+
 def transcribe(audio_path):
         
     speech_array, sampling_rate = librosa.load(audio_path, sr=16_000)