app.py

import spaces
from transformers import AutoModelForSeq2SeqLM,AutoTokenizer, pipeline
import gradio as grad
mdl_name = "NAMAA-Space/masrawy-english-to-egyptian-arabic-translator-v2.9"
# mdl = AutoModelForSeq2SeqLM.from_pretrained(mdl_name)
# my_tkn = AutoTokenizer.from_pretrained(mdl_name)
pipe = pipeline("translation", model=mdl_name, device = 'cuda')

@spaces.GPU
def translate(text):
    # inputs = my_tkn(text, return_tensors="pt")
    # trans_output = mdl.generate(**inputs)
    
    response = pipe(text)[0]['translation_text']

    #response = opus_translator(text)
    return response

input_textbox = grad.Textbox(lines=5, placeholder="Enter text to translate", label="Input Text")
output_textbox = grad.Textbox(lines=5, label="Egyption Arabic Translation")
grad.Interface(translate, inputs=[input_textbox], outputs=output_textbox).launch()