app.py

import torch
import gradio as gr
from transformers import pipeline

pipe = pipeline(task="automatic-speech-recognition", 
                model="deepakkumar07/whisper-small-tamil",
                device="cuda" if torch.cuda.is_available() else "cpu")

def transcribe(audio):
    text = pipe(audio)["text"]
    return text

iface = gr.Interface(
    fn=transcribe, 
    inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"), 
    outputs="text",
    title="Whisper Small Tamil",
    description="Realtime demo for Tamil speech recognition using a fine-tuned Whisper small model.",
)
if __name__ == "__main__":
    iface.launch()