tweaked initial NAR pass's initial token embeddings to use a different value, or osmething

vall_e/models/base.py

@@ -1024,11 +1024,15 @@ class Base(nn.Module):
 					embedding = self.tones_emb( input )
 				elif name == "resp":
 					if "len" in self.capabilities and quant_level == 0:
+						"""
 						# fill with "stop" tokens for NAR-only model
 						embedding = self.resps_emb(
 							torch.full_like(input if input.dim() == 1 else input[..., 0], self.stop_token),
 							offset = 0
 						)
+						"""
+						# fill with filler tokens for NAR-only model
+						embedding = self.dropout_token.repeat((input.shape[0], 1))
 					else:
 						# get RVQ level 0, or up to targetted RVQ level inference
 						if self.version <= 4: