Update gradio_app.py

gradio_app.py

@@ -3,7 +3,7 @@ from transformers import pipeline
 
 # Step 1: Load the pre-trained model
 # You can choose any suitable conversational model from the Hugging Face Model Hub
-chatbot = pipeline("conversational", model="microsoft/DialoGPT-small")
+chatbot = pipeline("conversational", model="microsoft/DialoGPT-large")
 
 # Step 2: Define the function that will process user input and return the model's response
 def respond(input_text):
@@ -20,26 +20,7 @@ iface = gr.Interface(
     description="Chat with an AI-powered bot based on a pre-trained model."  # A short description
 )
 
-# Inject custom CSS
-iface.launch(inline=True, share=True, css="""
-    body {
-        background-color: orange !important; /* Make sure this is applied */
-        border:10px solid white;
-    }
-    .container {
-        max-width: 800px !important; /* Limit the width of the container */
-        margin: auto;
-        padding: 20px;
-    }
-    .gr-input {
-        border: 2px solid #007bff !important; /* Use the correct class for Gradio input */
-        border-radius: 4px;
-    }
-    .gr-output {
-        color: black !important; /* Ensure this is not overridden */
-        font-size: 1.2em !important;
-    }
-""")
+
 
 # Step 4: Launch the interface
 if __name__ == "__main__":