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main_model.py

@@ -523,7 +523,7 @@ def load_models():
         print(f"Warning: {config.tokeniser_path} not found. Using default tokenizer.")
     
     # Load trained model first to get correct vocab size
-    checkpoint = torch.load(config.config.color_model_path, map_location=config.device)
+    checkpoint = torch.load(config.color_model_path, map_location=config.device)
     
     # Extract vocab size from the checkpoint's embedding layer
     vocab_size_from_checkpoint = checkpoint['text_encoder.embedding.weight'].shape[0]