Create app.py

app.py

@@ -0,0 +1,31 @@
+from transformers import pipeline
+import gradio as gr
+
+pipe = pipeline(model="Akseluhr/whisper-small-sv-Se-auhr-v2")
+
+
+def transcribe(rec=None, file=None):
+    if rec is not None:
+        audio = rec
+    elif file is not None:
+        audio = file
+    else:
+        return "Provide a recording or a file."
+
+    text = pipe(audio)["text"]
+    return text
+
+
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=[
+        gr.Audio(source="microphone", type="filepath", optional=True),
+        gr.Audio(source="upload", type="filepath", optional=True),
+    ],
+    outputs="text",
+    title="Whisper Small Swedish",
+    description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper model.",
+)
+
+
+iface.launch()