app.py

import gradio as gr
from transformers import pipeline

def transcribe_speech(filepath):
    model_id = "chaouch/whisper-small-dv"  # update with your model id
    pipe = pipeline("automatic-speech-recognition", model=model_id)
    output = pipe(
        filepath,
        max_new_tokens=256,
        generate_kwargs={
            "task": "transcribe",
            "language": "sinhalese",
        },  # update with the language you've fine-tuned on
        chunk_length_s=30,
        batch_size=8,
    )
    return output["text"]

if __name__ == "__main__":
    demo = gr.Interface(fn=transcribe_speech,
                        inputs=gr.Audio(sources="microphone", type="file"),
                        outputs=gr.Textbox())
    demo.launch(debug=True)