Update app.py

app.py

@@ -1,5 +1,5 @@
 import streamlit as st
-from transformers import pipeline
+from transformers import pipeline, AutoTokenizer, AutoModelForCasualLM
 import torch
 
 #Sidebar menu
@@ -20,13 +20,37 @@ if time_series:
 
 
 if chatbot:
+    
     st.header("Chat with me.")
+    text = st.text_area("Food security is a global challenge. Let's work together to find solutions. How can I help you today?")
+
+  
+    tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-9b-it")
+    model = AutoModelForCausalLM.from_pretrained(
+    "google/gemma-2-9b-it",
+    device_map="auto",
+    torch_dtype=torch.bfloat16)
     
-    pipe = pipeline("question-answering", model="google/gemma")
+   
     
+    if text:
+        input_ids = tokenizer(text, return_tensors="pt").to("cuda")
+        outputs = model.generate(**input_ids)
+        st.write(print(tokenizer.decode(outputs[0])))
+
+
+
+
+'''
+if chatbot:
+     
+    st.header("Chat with me.")
     text = st.text_area("Food security is a global challenge. Let's work together to find solutions. How can I help you today?")
 
+    pipe = pipeline("question-answering", model=model)
+    
     if text:
         out = pipe(text)
         st.write(out)
 
+'''