Update app.py

app.py

@@ -2,19 +2,21 @@ import streamlit as st
 from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
 from transformers import AutoModelForMaskedLM, AutoTokenizer
 
-model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-one-to-many-mmt")
-model = AutoModelForMaskedLM.from_pretrained("alabnii/jmedroberta-base-sentencepiece")
-model.eval()
-tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-one-to-many-mmt", src_large="en_XX")
-tokenizer = AutoTokenizer.from_pretrained("alabnii/jmedroberta-base-sentencepiece")
+# 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(text, return_tensors="pt")
-    generated_tokens = model.generate(
+    model_inputs = tokenizer_translation(text, return_tensors="pt")
+    generated_tokens = model_translation.generate(
         **model_inputs,
-        forced_bos_token_id=tokenizer.lang_code_to_id["hi_IN"]
+        forced_bos_token_id=tokenizer_translation.lang_code_to_id["hi_IN"]
     )
-    translation = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
-    st.json(translation)
+    translation = tokenizer_translation.batch_decode(generated_tokens, skip_special_tokens=True)
+    st.json(translation)