using pipeline

app.py

@@ -1,13 +1,10 @@
 import streamlit as st
 # Load model directly
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import pipeline
 
-tokenizer = AutoTokenizer.from_pretrained("openchat/openchat")
-model = AutoModelForCausalLM.from_pretrained("openchat/openchat")
-prompt = ""
-model_input = tokenizer(prompt, return_tensors="pt").to("cuda")
-response = tokenizer.decode(model.generate(**model_input,temperature=0.1, max_length=5000)[0], skip_special_tokens=True)
+classifier = pipeline("sentiment-analysis")
+output = classifier("We are very happy to show you the 🤗 Transformers library.")
 
 prompt = st.chat_input("Say something")
 if prompt:
-    st.write(f"User has sent the following prompt: {prompt}")
+    st.write(f"User has sent the following prompt: {output}")