add lazy

.streamlit/config.toml

@@ -0,0 +1,6 @@
+[theme]
+primaryColor="#FF8000"
+#backgroundColor="#FFFFFF"
+#secondaryBackgroundColor="#F0F2F6"
+#textColor="#262730"
+#font="sans serif"

app.py

@@ -5,8 +5,22 @@ from transformers import  AutoModelForSeq2SeqLM, MT5Tokenizer
 st.set_page_config(layout="wide", page_title="MT5 Persian Summary")
 
 
-fine = AutoModelForSeq2SeqLM.from_pretrained('nafisehNik/mt5-persian-summary')
-tokenizer = MT5Tokenizer.from_pretrained("nafisehNik/mt5-persian-summary")
+# Load model lazily
+@st.cache(allow_output_mutation=True)
+def load_model():
+    model = AutoModelForSeq2SeqLM.from_pretrained('nafisehNik/mt5-persian-summary')
+    return model
+
+# Load tokenizer lazily
+@st.cache(allow_output_mutation=True)
+def load_tokenizer():
+    tokenizer = MT5Tokenizer.from_pretrained("nafisehNik/mt5-persian-summary")
+    return tokenizer
+
+with st.spinner(text="Please wait while the model is loading...."):
+    # cache
+    fine = load_model()
+    tokenizer = load_tokenizer()
 
 
 # method for summary generation, using the global model and tokenizer