Change to use HF token

app.py

@@ -1,3 +1,4 @@
+import os
 from typing import Dict, Any
 
 import gradio as gr
@@ -50,18 +51,32 @@ if __name__ == "__main__":
     # Model configuration
     model_id = "Roblox/PII-OSS-Private-Not-Public"
 
+    # Get HF token from Hugging Face Space secrets
+    # In Spaces, set HF_TOKEN in Settings > Repository secrets
+    HF_TOKEN = os.getenv("HF_TOKEN")
+
     # Load model and tokenizer
-    # When deployed as a Hugging Face Space in the same organization,
-    # authentication is handled automatically
     print(f"Loading model: {model_id}")
     try:
-        model = AutoModelForSequenceClassification.from_pretrained(model_id)
-        tokenizer = AutoTokenizer.from_pretrained(model_id)
+        # Use token if available (required for private models)
+        if HF_TOKEN:
+            print("Using HF_TOKEN from environment/secrets")
+            model = AutoModelForSequenceClassification.from_pretrained(model_id, token=HF_TOKEN)
+            tokenizer = AutoTokenizer.from_pretrained(model_id, token=HF_TOKEN)
+        else:
+            print("No HF_TOKEN found, attempting without authentication...")
+            model = AutoModelForSequenceClassification.from_pretrained(model_id)
+            tokenizer = AutoTokenizer.from_pretrained(model_id)
+
         model.eval()
         print("Model loaded successfully!")
     except Exception as e:
         print(f"Failed to load model: {e}")
-        print("If running locally, you may need to login with: huggingface-cli login")
+        if not HF_TOKEN:
+            print("\n⚠️  For private models, you need to set HF_TOKEN as a Space secret:")
+            print("   1. Go to your Space Settings")
+            print("   2. Add a new secret named 'HF_TOKEN'")
+            print("   3. Set your Hugging Face token as the value")
         exit(1)
 
     # Create Gradio interface
@@ -82,4 +97,4 @@ if __name__ == "__main__":
         flagging_mode="never",
     )
 
-    demo.launch()
+    demo.launch()