diff --git a/vall_e/config.py b/vall_e/config.py
index d026e49..3e77416 100755
--- a/vall_e/config.py
+++ b/vall_e/config.py
@@ -164,6 +164,7 @@ class Model:
 	training: bool = True
 	interleave: bool = False
 	frozen_params: list[str] = field(default_factory=lambda: [])
+	p_ar_nar: float = 0.5
 
 	@property
 	def full_name(self):
diff --git a/vall_e/models/ar_nar.py b/vall_e/models/ar_nar.py
index dc73470..9a00646 100644
--- a/vall_e/models/ar_nar.py
+++ b/vall_e/models/ar_nar.py
@@ -88,7 +88,7 @@ class AR_NAR(Base):
 
 			# is training
 			if n_levels == self.n_resp_levels:
-				if random.random() < 0.95:
+				if random.random() < cfg.models.ar_nar.p_ar_nar:
 					quant_levels = None
 
 					targ_list = [r[..., 0] for r in resps_list] # guarantees we only have the first levels
diff --git a/vall_e/webui.py b/vall_e/webui.py
index b87356a..9872485 100644
--- a/vall_e/webui.py
+++ b/vall_e/webui.py
@@ -81,6 +81,9 @@ def do_inference( progress=gr.Progress(track_tqdm=True), *args, **kwargs ):
 
 	tmp = tempfile.NamedTemporaryFile(suffix='.wav')
 
+	if not args.references:
+		raise ValueError("No reference audio provided.")
+
 	tts = init_tts()
 	with timer() as t:
 		wav, sr = tts.inference(