Update app.py

app.py

@@ -2,8 +2,8 @@ import streamlit as st
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 
 # Load the model and tokenizer from Hugging Face Hub
-model_name = "teckmill/Jaleah-ai"  # Replace with your model repo name if needed
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+model_name = "microsoft/CodeGPT-small-py"  # Model name you provided
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
 # Initialize the pipeline
@@ -15,17 +15,18 @@ def generate_text(prompt):
     return generated[0]['generated_text']
 
 # Streamlit UI
-st.title("Jaleah AI - Text Generation")
-st.write("Enter a prompt to generate text:")
+st.title("CodeGPT Text Generation")
+st.write("Enter a prompt to generate code or text:")
 
 # Text input for the user to enter a prompt
-prompt = st.text_area("Prompt", "Once upon a time...")
+prompt = st.text_area("Prompt", "def example_function():\n    # Your code here...")
 
 # Button to trigger the model inference
-if st.button("Generate Text"):
+if st.button("Generate Code"):
     if prompt:
         generated_text = generate_text(prompt)
-        st.subheader("Generated Text")
+        st.subheader("Generated Code")
         st.write(generated_text)
     else:
-        st.warning("Please enter a prompt to generate text.")
+        st.warning("Please enter a prompt to generate code.")
+