Update app.py

app.py

@@ -3,12 +3,12 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 from huggingface_hub import Repository
 import os
 
-# Retrieve the Hugging Face token from Streamlit secrets
-token = st.secrets["HUGGINGFACE_TOKEN"]  # Ensure your secret key is "HUGGINGFACE_TOKEN"
+# Retrieve Hugging Face token from Streamlit secrets
+token = st.secrets["HUGGINGFACE_TOKEN"]  # Make sure to add your Hugging Face token to Streamlit secrets
 
 # Define model directory and Hugging Face repo name
-model_dir = "./tuned_model"  # Directory where the fine-tuned model is saved
-repo_name = "krisha06/Python_tutor"  # Replace with your Hugging Face repo name
+model_dir = "./tuned_model"  # The directory where the fine-tuned model is saved
+repo_name = "user06/Python_tutor"  # Replace with your Hugging Face repo name
 
 # Streamlit App Title
 st.title("AI Coding Mentor")
@@ -23,7 +23,7 @@ if upload_model_button:
     if os.path.exists(model_dir):
         # Initialize the Hugging Face Repository and push model to the Hub
         repo = Repository(local_dir=model_dir, clone_from=repo_name)
-        repo.push_to_hub(token=token)  # Use the token from Streamlit secrets
+        repo.push_to_hub(token=token)  # Use the token for authentication
         st.success("Model uploaded to Hugging Face Hub successfully!")
     else:
         st.error("Model directory does not exist. Please make sure the model is fine-tuned first.")
@@ -35,7 +35,7 @@ st.header("Ask Me Any Coding Question!")
 model_name = repo_name  # Use the repo name if the model is on Hugging Face Hub, else use local dir
 
 if os.path.exists(model_dir):
-    # Load the model and tokenizer from the local directory
+    # Load the model and tokenizer from local directory
     model = AutoModelForCausalLM.from_pretrained(model_dir, use_auth_token=token)
     tokenizer = AutoTokenizer.from_pretrained(model_dir, use_auth_token=token)
 else: