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import streamlit as st
import torch
import pickle
from transformers import MarianMTModel, MarianTokenizer
# Load the trained model
with open("nmt_model.pkl", "rb") as f:
model = pickle.load(f)
tokenizer = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ar-en")
# Streamlit UI
st.title("Arabic to English Translator")
st.write("Enter Arabic text and get the English translation.")
arabic_text = st.text_area("Enter Arabic Text:")
if st.button("Translate"):
if arabic_text:
# Tokenize and translate
inputs = tokenizer(arabic_text, return_tensors="pt", padding=True, truncation=True, max_length=128)
with torch.no_grad():
translated_ids = model.generate(**inputs)
translated_text = tokenizer.batch_decode(translated_ids, skip_special_tokens=True)[0]
st.subheader("Translated English Text:")
st.write(translated_text)
else:
st.warning("Please enter Arabic text.")
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