Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+import time
+from transformers import pipeline
+
+p = pipeline("automatic-speech-recognition", 
+             model = 'carlosdanielhernandezmena/whisper-large-faroese-8k-steps-100h-ct2')
+
+def transcribe(audio, state=""):
+    time.sleep(3)
+    text = p(audio)["text"]
+    state += text + " "
+    return state, state
+
+    
+gr.Interface(
+    fn=transcribe, 
+    inputs=[
+        gr.inputs.Audio(source="microphone", type="filepath"),
+        'state'
+    ],
+    outputs=[
+        "textbox",
+        "state"
+    ],
+    live=True).launch()