app.py

# import gradio as gr

# model_interface = gr.Interface.load("models/jonatasgrosman/wav2vec2-large-xlsr-53-arabic", wait=True)
# model_interface.launch()
# Use a pipeline as a high-level helper


from transformers import pipeline
import gradio as gr

pipe = pipeline(model="jonatasgrosman/wav2vec2-large-xlsr-53-arabic")  # 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",
    
)

iface.launch()