update app.py

app.py

@@ -28,19 +28,13 @@ tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id)
 
 # Create text generation pipeline
-pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+pipe = pipeline(model = model, tokenizer = tokenizer)
 
 
-prompt = st.text_input("Please ask your question here:")
-
-
-
-if prompt := st.chat_input("Please ask your question here:"):
-        # Display user message in chat message container
-        st.chat_message("user").markdown("<b style='color:Red;'>"+prompt+"</b>", unsafe_allow_html=True)
-        # Add user message to chat history
-        st.session_state.query = prompt
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        # Generate response
-        result = pipe(prompt)#, max_length=100, num_return_sequences=1)
-        
+with st.form('my_form'):
+    question = st.text_area('Enter your question:', 'Tell me about attention mechanisms in a transformer?')
+    submitted = st.form_submit_button('Submit')
+    if submitted:
+        result = pipe(question, max_length=100)
+        st.write(question)
+        st.write(result[0]['generated_text'])