diff --git a/src/utils.py b/src/utils.py
index 401794a..d4b9c89 100755
--- a/src/utils.py
+++ b/src/utils.py
@@ -543,7 +543,12 @@ def setup_tortoise(restart=False):
 		tts = None
 
 	print(f"Initializating TorToiSe... (using model: {args.autoregressive_model})")
-	tts = TextToSpeech(minor_optimizations=not args.low_vram, autoregressive_model_path=args.autoregressive_model)
+	try:
+		tts = TextToSpeech(minor_optimizations=not args.low_vram, autoregressive_model_path=args.autoregressive_model)
+	except Exception as e:
+		tts = TextToSpeech(minor_optimizations=not args.low_vram)
+		load_autoregressive_model(args.autoregressive_model)
+
 	get_model_path('dvae.pth')
 	print("TorToiSe initialized, ready for generation.")
 	return tts
@@ -826,7 +831,25 @@ def update_autoregressive_model(path_name):
 		raise Exception("TTS is uninitialized or still initializing...")
 
 	print(f"Loading model: {path_name}")
-	tts.load_autoregressive_model(path_name)
+
+	if hasattr(tts, 'load_autoregressive_model') and tts.load_autoregressive_model(path_name):
+		tts.load_autoregressive_model(path_name)
+	# polyfill in case a user did NOT update the packages
+	else:
+		from tortoise.models.autoregressive import UnifiedVoice
+
+		tts.autoregressive_model_path = autoregressive_model_path if autoregressive_model_path and os.path.exists(autoregressive_model_path) else get_model_path('autoregressive.pth', tts.models_dir)
+
+		del tts.autoregressive
+		tts.autoregressive = UnifiedVoice(max_mel_tokens=604, max_text_tokens=402, max_conditioning_inputs=2, layers=30,
+										  model_dim=1024,
+										  heads=16, number_text_tokens=255, start_text_token=255, checkpointing=False,
+										  train_solo_embeddings=False).cpu().eval()
+		tts.autoregressive.load_state_dict(torch.load(tts.autoregressive_model_path))
+		tts.autoregressive.post_init_gpt2_config(kv_cache=tts.use_kv_cache)
+		if tts.preloaded_tensors:
+			tts.autoregressive = tts.autoregressive.to(tts.device)
+
 	print(f"Loaded model: {tts.autoregressive_model_path}")
 	
 	args.autoregressive_model = path_name