commit

app.py

@@ -1,5 +1,3 @@
-#%%
-from huggingface_hub import login
 from transformers import pipeline
 from datasets import load_dataset
 import gradio as gr
@@ -12,18 +10,15 @@ num_examples = 3
 examples_atco2   = [ [{'sampling_rate': atco2[i]['audio']['sampling_rate'], 'raw': atco2[i]['audio']['array']}, False, 'large-v3'] for i in range(num_examples)]
 #examples_atcosim = [ [{'sampling_rate': atcosim[i]['audio']['sampling_rate'], 'raw': atcosim[i]['audio']['array']}, False, 'large-v3'] for i in range(num_examples)]
 examples = examples_atco2 #+ examples_atcosim
-# examples = [atco2[0]['audio']['array'], atcosim[0]['audio']['array'], atco2[1]['audio']['array'], atcosim[1]['audio']['array'], atco2[2]['audio']['array'], atcosim[2]['audio']['array']]
-# examples_labels = ['Example ' + str(i+1) for i in range(len(examples))]
 
 whisper = pipeline(model='jlvdoorn/whisper-large-v3-atco2-asr-atcosim')
-#%%
+
 def transcribe(audio, model_version):
     if audio is not None:
         return whisper(audio)['text']
     else:
         return 'There was no audio to transcribe...'
 
-#%%
 file_iface = gr.Interface(
     fn = transcribe,
     inputs = [gr.Audio(source='upload', interactive=True),
@@ -48,6 +43,6 @@ mic_iface = gr.Interface(
     title = 'Whisper ATC - Large v3',
     description = 'Transcribe ATC speech',
 )
-#%%
+
 demo = gr.TabbedInterface([file_iface, mic_iface], ["File", "Microphone"])
-demo.launch()
+demo.launch(server_name='0.0.0.0')