correct model load

app.py

@@ -6,6 +6,8 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Detect execution environment: Spaces runs as user 'gradio'
 is_space = (getpass.getuser() == "gradio")
+print("RUNNING AS USER:", getpass.getuser())
+
 
 # Choose model checkpoints based on environment
 if is_space:
@@ -21,19 +23,21 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 
 # Load tokenizer and model (with fallback on Spaces)
 def load_model():
-    if not is_space:
-        tokenizer = AutoTokenizer.from_pretrained(primary_checkpoint)
-        model = AutoModelForCausalLM.from_pretrained(primary_checkpoint).to(device)
-        return tokenizer, model, primary_checkpoint
+    print(f"🔍 Trying to load PRIMARY: {primary_checkpoint}")
     try:
         tokenizer = AutoTokenizer.from_pretrained(primary_checkpoint)
-        model = AutoModelForCausalLM.from_pretrained(primary_checkpoint).to(device)
+        model     = AutoModelForCausalLM.from_pretrained(primary_checkpoint).to(device)
+        print("✅ Loaded PRIMARY ✓")
         return tokenizer, model, primary_checkpoint
-    except Exception:
-        # Fallback path on Spaces
-        tokenizer = AutoTokenizer.from_pretrained(fallback_checkpoint)
-        model = AutoModelForCausalLM.from_pretrained(fallback_checkpoint).to(device)
-        return tokenizer, model, fallback_checkpoint
+    except Exception as e:
+        print("❌ PRIMARY failed:", e)
+        if fallback_checkpoint:
+            print(f"🔁 Falling back to {fallback_checkpoint}")
+            tokenizer = AutoTokenizer.from_pretrained(fallback_checkpoint)
+            model     = AutoModelForCausalLM.from_pretrained(fallback_checkpoint).to(device)
+            print("✅ Loaded FALLBACK ✓")
+            return tokenizer, model, fallback_checkpoint
+        raise
 
 tokenizer, model, model_name = load_model()
 
@@ -134,6 +138,8 @@ hotel_ids = [
 demo = gr.Blocks()
 with demo:
     gr.Markdown("### 🏨 Hotel Chatbot Demo")
+    gr.Markdown(f"Currently running: **{model_name}**", elem_id="model‑status")
+
     with gr.Row():
         hotel_selector = gr.Dropdown(hotel_ids, label="Choose a hotel", value=hotel_ids[0])
     chatbot = gr.Chatbot()