Update app.py

app.py

@@ -22,10 +22,24 @@ if audio_bytes:
     
 
 pipe_p=pipeline(model="ramsrigouthamg/t5_sentence_paraphraser")
+st.title("Paraphraser")
 import sentencepiece as spm
 sp=spm.SentencePieceProcessor(model_file='t5_sentence_paraphraser/spiece.model')
 st.title("Paraphraser")
 text_p=st.text_area('Input sentence:')
 if text_p:
     out_p=pipe_p(text_p)
-    st.text_area(label="Output sentence:", value=out_p)
+    st.text_area(label="Output sentence:", value=out_p)
+
+from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
+st.title("Language Translator")
+model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
+tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
+tokenizer.src_lang = "en_XX"
+text_l=st.text_area('Input sentence:')
+encoded_en = tokenizer(text_l, return_tensors="pt")
+generated_tokens = model.generate(
+    **encoded_en,
+    forced_bos_token_id=tokenizer.lang_code_to_id["hi_IN"]
+)
+tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)