diff --git a/vall_e/models/base.py b/vall_e/models/base.py
index 9cf3796..533c678 100755
--- a/vall_e/models/base.py
+++ b/vall_e/models/base.py
@@ -223,7 +223,7 @@ class AudioEmbedding(nn.Module):
 
 		return embedding
 
-	def internal_forward(self, xi: Tensor, offset: int | None = None, quant_level: int | None = None ) -> Tensor:
+	def internal_forward(self, xi: Tensor, offset: int | None = None, quant_level: int | None = None, sums = None ) -> Tensor:
 		if offset is None:
 			# prom
 			if self.capabilities is None:
@@ -236,6 +236,9 @@ class AudioEmbedding(nn.Module):
 			elif quant_level > 0:
 				offset = 1
 
+		if sums is None:
+			sums = self.sums
+
 		if quant_level is None:
 			quant_level = 0 if xi.dim() == 1 else xi.shape[-1] - 1
 		
@@ -247,8 +250,8 @@ class AudioEmbedding(nn.Module):
 
 		return x
 
-	def forward(self, xi: Tensor, offset: int | None = None, quant_level: int | None = None ) -> Tensor:
-		x = self.internal_forward( xi, offset = offset, quant_level = quant_level ) if self.external_mode != "exclusive" or xi.shape[0] == 0 else None
+	def forward(self, xi: Tensor, offset: int | None = None, quant_level: int | None = None, sums = None ) -> Tensor:
+		x = self.internal_forward( xi, offset = offset, quant_level = quant_level, sums = sums ) if self.external_mode != "exclusive" or xi.shape[0] == 0 else None
 
 		if self.external_mode and xi.shape[0] > 0:
 			external_embeddings = self.external_embeddings( xi, quant_level = quant_level )
@@ -1093,10 +1096,12 @@ class Base(nn.Module):
 							)
 					# cheat-y way to handle performing STT across all levels
 					elif task_type in summed_embeddings_task:
+						# we do a manual sum because I trained it to use the AR embeddings + NAR embeddings for STT......
 						embedding = sum([ self.resps_emb(
 							input[:, :l+1],
 							offset = 0 if l == 0 else 1, # or maybe set to 1
-							quant_level = l
+							quant_level = l,
+							sums = False
 						) for l in range( input.shape[-1] - 1 ) ])
 					else:
 						# get RVQ level 0, or up to targetted RVQ level inference
diff --git a/vall_e/webui.py b/vall_e/webui.py
index 3a143b4..dc7ea97 100644
--- a/vall_e/webui.py
+++ b/vall_e/webui.py
@@ -226,13 +226,11 @@ def do_inference_stt( progress=gr.Progress(track_tqdm=True), *args, **kwargs ):
 	args.references = args.references.split(";") if args.references is not None else []
 	if args.max_ar_steps == 0:
 		for i, path in enumerate( args.references ):
-			print(i, path)
 			metadata = torchaudio.info(path)
 			duration = metadata.num_frames / metadata.sample_rate
 			args.max_ar_steps += duration
 		args.max_ar_steps = math.floor( args.max_ar_steps * 20 ) # assume 20 tokens per second
 
-
 	tts = init_tts()
 	
 	gr.Info("Inferencing...")