Upload app.py

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+from transformers import pipeline
+
+pipeline = pipeline(model="openai/whisper-medium.en")
+
+def transcribe(file):
+    options = dict(task="transcribe", best_of=5)
+    text = model.transcribe(file, **options)["text"]
+    return text.strip()
+
+block = gr.Blocks()
+
+with block:
+    with gr.Group():
+        audio = gr.Audio(
+            show_label=False,
+            source="microphone",
+            type="filepath"
+        )
+        with gr.Box():
+            with gr.Row().style(equal_height=True):
+                transcribe_button = gr.Button("Transcribe")
+        
+        textbox = gr.Textbox(show_label=False)
+        
+        transcribe_button.click(transcribe, inputs=[audio], outputs=[textbox])
+ 
+block.launch(share=True)