app.py

from transformers import pipeline
import gradio as gr

pipe = pipeline(model="NS-Y/whisper-tiny-he-ex", generate_kwargs = {"language":"<|he|>","task": "transcribe"})  # change to "your-username/the-name-you-picked"

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

iface = gr.Interface(
    fn=transcribe,
    inputs=gr.Audio(source="upload", type="filepath"),
    outputs="text",
    title="NS-Y/whisper-tiny-he-ex",
    description="Realtime demo for Hebrew speech recognition using a fine-tuned NS-Y/whisper-tiny-he-ex.",
)

iface.launch(share=True)