import streamlit as st from transformers import MBartForConditionalGeneration, MBart50TokenizerFast from transformers import AutoModelForMaskedLM, AutoTokenizer # Load the models and tokenizers model_translation = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-one-to-many-mmt") model_masked_lm = AutoModelForMaskedLM.from_pretrained("alabnii/jmedroberta-base-sentencepiece") model_translation.eval() tokenizer_translation = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-one-to-many-mmt", src_lang="en_XX") tokenizer_masked_lm = AutoTokenizer.from_pretrained("alabnii/jmedroberta-base-sentencepiece") text = st.text_area('Enter the text:') if text: model_inputs = tokenizer_translation(text, return_tensors="pt") lg = st.text_input("Select Language: hi.Hindi, te.Telugu, gu.Gujarati, bn.Bengali") if lg=='hi': generated_tokens = model_translation.generate( **model_inputs, forced_bos_token_id=tokenizer_translation.lang_code_to_id["hi_IN"] ) translation = tokenizer_translation.batch_decode(generated_tokens, skip_special_tokens=True) st.write(translation) elif lg=='te': generated_tokens = model_translation.generate( **model_inputs, forced_bos_token_id=tokenizer_translation.lang_code_to_id["te_IN"] ) translation = tokenizer_translation.batch_decode(generated_tokens, skip_special_tokens=True) st.write(translation) elif lg=='gu': generated_tokens = model_translation.generate( **model_inputs, forced_bos_token_id=tokenizer_translation.lang_code_to_id["gu_IN"] ) translation = tokenizer_translation.batch_decode(generated_tokens, skip_special_tokens=True) st.write(translation) elif lg=='bn': generated_tokens = model_translation.generate( **model_inputs, forced_bos_token_id=tokenizer_translation.lang_code_to_id["bn_IN"] ) translation = tokenizer_translation.batch_decode(generated_tokens, skip_special_tokens=True) st.json(translation) else: st.write('invalid choice!')