Enhance logging in load_model function

app.py

@@ -22,14 +22,14 @@ def apply_custom_css():
 def load_model():
     model_path = "HuggingFaceH4/zephyr-7b-beta"
     peft_model_path = "yitzashapiro/FDA-guidance-zephyr-7b-beta-PEFT"
-    
+
     try:
         HF_API_TOKEN = os.getenv("HF_API_TOKEN")
         st.write("Loading tokenizer...")
         tokenizer = AutoTokenizer.from_pretrained(
             model_path,
             trust_remote_code=True,
-            use_auth_token=HF_API_TOKEN
+            use_auth_token=HF_API_TOKEN  # Use token for private models
         )
         st.write("Loading model...")
         model = AutoModelForCausalLM.from_pretrained(
@@ -37,7 +37,7 @@ def load_model():
             device_map="auto",
             torch_dtype=torch.float16,
             trust_remote_code=True,
-            use_auth_token=HF_API_TOKEN
+            use_auth_token=HF_API_TOKEN  # Use token for private models
         ).eval()
         st.write("Loading PEFT adapter...")
         model.load_adapter(peft_model_path)
@@ -45,9 +45,10 @@ def load_model():
     except Exception as e:
         st.error(f"Error loading model: {e}")
         st.stop()
-    
+
     return tokenizer, model
 
+
 def generate_response(tokenizer, model, user_input):
     messages = [
         {"role": "user", "content": user_input}