app.py

import gradio as gr
import mlx_whisper

def transcribe(audio):
    text = mlx_whisper.transcribe(
        audio,
        path_or_hf="Kimang18/whisper-tiny-khmer-mlx-fp32",
        fp16=False,
        condition_on_previous_text=False,
    )['text']
    return text

iface = gr.Interface(
    fn=transcribe,
    inputs=gr.Audio(type="filepath", waveform_options={"sample_rate": 16000}),
    outputs="text",
    title="Whisper Tiny Khmer",
    description="Realtime demo for Khmer speech transcription using a fine-tuned Whisper tiny model.",
)

iface.launch(share=False)