Create app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from transformers import pipeline
+
+# Initialize the pipeline with the specified model
+pipe = pipeline(model="Lingalingeswaran/whisper-small-sinhala")
+
+def transcribe(audio):
+    # Transcribe the audio file to text
+    text = pipe(audio)["text"]
+    return text
+
+# Create the Gradio interface
+
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"),
+    outputs="text",
+    title="Whisper Small Sinhala",
+    description="Realtime demo for Sinhala speech recognition using a fine-tuned Whisper small model.",
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch()