Create app.py

app.py

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+import streamlit as st
+from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
+
+# Load pre-trained model and tokenizer
+model_name = "ahmed792002/Finetuning_MBart_English_Arabic_Translation"
+model = MBartForConditionalGeneration.from_pretrained(model_name)
+tokenizer = MBart50TokenizerFast.from_pretrained(model_name)
+
+# Streamlit App
+st.title("English to Arabic Translation")
+st.write("Enter text in English to translate it to Arabic:")
+
+# Input box for English text
+english_text = st.text_area("Enter English Text")
+
+# Translate the text when the button is clicked
+if st.button("Translate"):
+    if english_text:
+        # Tokenize the input
+        inputs = tokenizer(english_text, return_tensors="pt", padding=True)
+        
+        # Generate translation
+        translated = model.generate(**inputs)
+        
+        # Decode the translated text
+        translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
+        
+        # Display the translated text
+        st.write(f"Translated text: {translated_text}")
+    else:
+        st.write("Please enter some English text to translate.")