Update app.py

app.py

@@ -3,9 +3,8 @@ import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Load the model and tokenizer
-model_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+model_id = "google/gemma-7b"  # Replace with "google/gemma-7b-it" for instruction tuning
 tokenizer = AutoTokenizer.from_pretrained(model_id)
-
 model = AutoModelForCausalLM.from_pretrained(model_id)
 
 # Function to generate responses based on user messages
@@ -16,11 +15,9 @@ def generate_response(messages):
     return generated_response
 
 # Streamlit app
-st.title("Mixtral Chatbot")
-
+st.title("Gemma Chatbot")
 messages = []
 user_input = st.text_input("You:", "")
-
 if st.button("Send"):
     if user_input:
         messages.append({"role": "user", "content": user_input})
@@ -34,4 +31,4 @@ for message in messages:
     if message["role"] == "user":
         st.text_input("You:", value=message["content"], disabled=True)
     elif message["role"] == "assistant":
-        st.text_area("Mixtral:", value=message["content"], disabled=True)
+        st.text_area("Gemma:", value=message["content"], disabled=True)