fix: set all_tied_weights_keys for transformers 5.6 compatibility

modeling_spatial_embeddings.py

@@ -143,10 +143,15 @@ class EmbeddingProjector(nn.Module):
 
 class SpatialEmbeddingsModel(PreTrainedModel):
     config_class = SpatialEmbeddingsConfig
+    _tied_weights_keys = []
 
     def __init__(self, config: SpatialEmbeddingsConfig):
         super().__init__(config)
         self.config = config
+        # transformers ≥5.6 accesses all_tied_weights_keys before tie_weights() is called
+        # for custom trust_remote_code models; set it here since we have no tied weights.
+        if not hasattr(self, "all_tied_weights_keys"):
+            self.all_tied_weights_keys = {}
 
         # Initialize backbone from config rather than from_pretrained.
         # Calling from_pretrained inside __init__ is an anti-pattern in transformers ≥5: