app.py

import streamlit as st
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
from transformers import MBartForConditionalGeneration, MBart50TokenizerFast

def main():
    st.title("Translation App")

    # Load model and tokenizer
    model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-one-to-many-mmt")
    tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-one-to-many-mmt", src_lang="en_XX")

    # Input text area
    input_text = st.text_area("Enter text to translate", "")

    if st.button("Translate"):
        # Perform translation
        translated_text = translate_text(input_text, model, tokenizer)

        # Display translated text
        st.write("Translated Text:")
        st.write(translated_text)

def translate_text(input_text, model, tokenizer):
    # Tokenize input text
    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
    generated_tokens = model.generate(
    **input_ids,
    forced_bos_token_id=tokenizer.lang_code_to_id["hi_IN"]
)

    # Decode translated text
    translated_text = tokenizer.decode(generated_tokens[0], skip_special_tokens=True)

    return translated_text

if __name__ == '__main__':
    main()