adding HF token

app.py

@@ -8,6 +8,7 @@ Two-stage hierarchical cascade:
 Models were trained on APS PhySH labels with google/embeddinggemma-300m embeddings.
 """
 
+import os
 import re
 from pathlib import Path
 from typing import Dict, List, Tuple
@@ -94,7 +95,10 @@ def load_models():
         device = "cpu"
 
     print(f"Loading embedding model ({EMBEDDING_MODEL_NAME}) on {device} …")
-    embedding_model = SentenceTransformer(EMBEDDING_MODEL_NAME, device=device)
+    hf_token = os.environ.get("HF_TOKEN")
+    embedding_model = SentenceTransformer(
+        EMBEDDING_MODEL_NAME, device=device, token=hf_token,
+    )
 
     # --- discipline model ---
     disc_ckpt = torch.load(DISCIPLINE_MODEL_PATH, map_location=device, weights_only=False)