Update app.py

app.py

@@ -37,16 +37,18 @@ content_models = {
 # Load the translation model and tokenizer locally
 @st.cache_resource
 def load_translation_model():
-    model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-one-mmt")
-    tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-one-mmt")
+    with st.spinner('Loading translation model... Please wait.'):
+        model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-one-mmt")
+        tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-one-mmt")
     return model, tokenizer
 
 # Function to perform translation locally
 def translate_text_local(text):
     model, tokenizer = load_translation_model()
-    inputs = tokenizer(text, return_tensors="pt", max_length=512, truncation=True)
-    translated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.lang_code_to_id["en_XX"])
-    translated_text = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
+    with st.spinner('Translation is on progress... Please wait.'):
+        inputs = tokenizer(text, return_tensors="pt", max_length=512, truncation=True)
+        translated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.lang_code_to_id["en_XX"])
+        translated_text = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
     return translated_text
 
 # Function to query Groq content generation model (optional)