Create app.py

app.py

@@ -0,0 +1,15 @@
+from transformers import pipeline
+import librosa
+import gradio as gr
+
+def pipeline_predict(input):
+  classifier = pipeline("audio-classification", model="santhosh-4000/wav2vec2-base-finetuned-mednames")
+  return classifier(input)
+
+def gradio_predict(audio):
+  audio, rate = librosa.load(audio, sr=librosa.get_samplerate(audio))
+  output = pipeline_predict(audio)
+  return output
+
+iface = gr.Interface(fn=gradio_predict, inputs=gr.Audio(source='microphone', type='filepath'), outputs="text")
+iface.launch(debug=True)