Update app.py

app.py

@@ -1,6 +1,6 @@
 import streamlit as st
-import torch
 from transformers import pipeline
+import torch
 import csv
 import re
 import warnings
@@ -14,17 +14,13 @@ MAGICODER_PROMPT = """You are an exceptionally intelligent coding assistant that
 @@ Response
 """
 
-# Load Magicoder model and apply dynamic quantization
+# Create a text generation pipeline using the Magicoder model, text-generation task, bfloat16 torch data type and auto device mapping.
 generator = pipeline(
     model="ise-uiuc/Magicoder-S-DS-6.7B",
     task="text-generation",
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
 )
-quantized_generator = torch.quantization.quantize_dynamic(
-    generator.model,
-    {torch.nn.Linear},
-    dtype=torch.qint8
-)
-generator.model = quantized_generator
 
 # Function to generate response
 def generate_response(instruction):
@@ -41,6 +37,16 @@ def save_to_csv(data, filename):
         writer = csv.writer(csvfile)
         writer.writerow(data)
 
+# Function to process user feedback
+def process_output(correct_output):
+    if correct_output.lower() == 'yes':
+        feedback = st.text_input("Do you want to provide any feedback?")
+        save_to_csv(["Correct", feedback], 'output_ratings.csv')
+    else:
+        correct_code = st.text_area("Please enter the correct code:")
+        feedback = st.text_input("Any other feedback you want to provide:")
+        save_to_csv(["Incorrect", feedback, correct_code], 'output_ratings.csv')
+
 # Streamlit app
 def main():
     st.title("Magicoder Assistant")
@@ -52,13 +58,7 @@ def main():
         st.text(generated_response)
 
         correct_output = st.radio("Is the generated output correct?", ("Yes", "No"))
-        if correct_output.lower() == 'yes':
-            feedback = st.text_input("Do you want to provide any feedback?")
-            save_to_csv(["Correct", feedback], 'output_ratings.csv')
-        else:
-            correct_code = st.text_area("Please enter the correct code:")
-            feedback = st.text_input("Any other feedback you want to provide:")
-            save_to_csv(["Incorrect", feedback, correct_code], 'output_ratings.csv')
+        process_output(correct_output)
 
 if __name__ == "__main__":
     main()