diff --git a/codes/data/__init__.py b/codes/data/__init__.py
index 53f3c309..1ad2762e 100644
--- a/codes/data/__init__.py
+++ b/codes/data/__init__.py
@@ -89,7 +89,7 @@ def create_dataset(dataset_opt, return_collate=False):
     elif mode == 'grand_conjoined_voice':
         from data.audio.grand_conjoined_dataset import GrandConjoinedDataset as D
         from data.zero_pad_dict_collate import ZeroPadDictCollate as C
-        if opt_get(dataset_opt, ['needs_collate'], True):
+        if opt_get(dataset_opt, ['needs_collate'], False):
             collate = C()
     else:
         raise NotImplementedError('Dataset [{:s}] is not recognized.'.format(mode))
diff --git a/codes/models/gpt_voice/gpt_asr_hf2.py b/codes/models/gpt_voice/gpt_asr_hf2.py
index d315cbae..ea4b5303 100644
--- a/codes/models/gpt_voice/gpt_asr_hf2.py
+++ b/codes/models/gpt_voice/gpt_asr_hf2.py
@@ -288,7 +288,7 @@ class GptAsrHf2(nn.Module):
             mel_len = 0
         else:
             mel_emb = self.mel_encoder(mel_inputs)
-            assert mel_emb.shape[1] <= self.max_mel_frames
+            assert mel_emb.shape[1] <= self.max_mel_frames, f'{mel_emb.shape[1]} > {self.max_mel_frames}'
             mel_emb = mel_emb.permute(0,2,1).contiguous()
             mel_emb = mel_emb + self.mel_pos_embedding(torch.arange(mel_emb.shape[1], device=mel_emb.device))
             emb = torch.cat([mel_emb, text_emb], dim=1)
@@ -303,8 +303,8 @@ class GptAsrHf2(nn.Module):
         return text_logits
 
     def forward(self, mel_inputs, text_inputs, return_attentions=False):
-        assert text_inputs.shape[1] <= self.max_symbols_per_phrase
-        assert text_inputs.max() <= self.number_text_tokens
+        assert text_inputs.shape[1] <= self.max_symbols_per_phrase, str(text_inputs.shape[1])
+        assert text_inputs.max() <= self.number_text_tokens, str(text_inputs.max())
 
         text_inputs, text_targets = self.build_aligned_inputs_and_targets(text_inputs, self.start_token, self.stop_token)
         text_emb = self.gpt.get_input_embeddings()(text_inputs) + \
@@ -317,8 +317,8 @@ class GptAsrHf2(nn.Module):
         return loss_text.mean(), text_logits
 
     def text_only(self, text_inputs):
-        assert text_inputs.shape[1] <= self.max_symbols_per_phrase
-        assert text_inputs.max() <= self.number_text_tokens
+        assert text_inputs.shape[1] <= self.max_symbols_per_phrase, str(text_inputs.shape[1])
+        assert text_inputs.max() <= self.number_text_tokens, str(text_inputs.max())
 
         text_inputs, text_targets = self.build_aligned_inputs_and_targets(text_inputs, self.start_token, self.stop_token)
         text_emb = self.gpt.get_input_embeddings()(text_inputs) + \