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import gradio as gr | |
from transformers import pipeline | |
# Load the pre-trained translation model | |
translator = pipeline("translation_en_to_ur", model="Helsinki-NLP/opus-mt-en-ur") | |
# Translation function | |
def translate_text(text): | |
translation = translator(text, max_length=400) | |
return translation[0]['translation_text'] | |
# Gradio interface | |
interface = gr.Interface( | |
fn=translate_text, | |
inputs=gr.Textbox(lines=2, placeholder="Enter English text here..."), | |
outputs=gr.Textbox(lines=2, label="Urdu Translation"), | |
title="English to Urdu Translation", | |
description="Translate English text to Urdu using a pre-trained model." | |
) | |
# Launch the app | |
if __name__ == "__main__": | |
interface.launch() |