Updated app.py to run in HF Spaces

app.py

@@ -6,9 +6,15 @@ import os
 # print(os.environ['hf_token'])
 ## Try to load a local model if available
 try:
-	whisper = pipeline(model='/mnt/projects/whisper/WhisperANSP/Models/whisper-large-v2-atco2-asr-atcosim-ANSP-3h1m', task='automatic-speech-recognition')
+    whisper = pipeline(model='/mnt/projects/whisper/WhisperANSP/Models/whisper-large-v2-atco2-asr-atcosim-ANSP-3h1m', task='automatic-speech-recognition')
+    ttl = 'Whisper Large v2 - ATCO2-ATCOSIM-ANSP'
+    dis = 'This demo will transcribe ATC audio files by using the Whisper Large v2 model fine-tuned on the ATCO2, ATCOSIM and ANSP datasets. \n \n Further it uses a Named Entity Recognition model to extract callsigns, commands and values from the transcription. \n This model is based on Google\'s BERT model and fine-tuned on the ATCO2 dataset.'
+
 except:
-    whisper = pipeline(model='jlvdoorn/whisper-large-v2-atco2-asr-atcosim')
+    whisper = pipeline(model='jlvdoorn/whisper-large-v2-atco2-asr-atcosim', use_auth_token=os.environ['hf_token'], task='automatic-speech-recognition')
+    ttl = 'Whisper Large v2 - ATCO2-ATCOSIM'
+    dis = 'This demo will transcribe ATC audio files by using the Whisper Large v2 model fine-tuned on the ATCO2 and ATCOSIM datasets. \n \n Further it uses a Named Entity Recognition model to extract callsigns, commands and values from the transcription. \n This model is based on Google\'s BERT model and fine-tuned on the ATCO2 dataset.'
+
 bert_atco_ner = pipeline(model='Jzuluaga/bert-base-ner-atc-en-atco2-1h')
 
 #%%
@@ -53,8 +59,8 @@ iface = gr.Interface(
         fn=transcribeAndExtract,
         inputs=[gr.Audio(source='upload', type='filepath', interactive=True), gr.Audio(source='microphone', type='filepath'), gr.Checkbox(label='Transcribe only', default=False)],
         outputs=[gr.Text(label='Transcription'), gr.Text(label='Callsigns, commands and values')],
-        title='Whisper Large v2 - ATCO2-ATCOSIM-ANSP',
-        description='This demo will transcribe ATC audio files by using the Whisper Large v2 model fine-tuned on the ATCO2, ATCOSIM and ANSP datasets. \n \n Further it uses a Named Entity Recognition model to extract callsigns, commands and values from the transcription. \n This model is based on Google\'s BERT model and fine-tuned on the ATCO2 dataset.',
+        title=ttl,
+        description=dis,
 )
 
 #%%