diff --git a/funasr/models/llm_asr/model.py b/funasr/models/llm_asr/model.py
index 7b04d754d..11acfde7b 100644
--- a/funasr/models/llm_asr/model.py
+++ b/funasr/models/llm_asr/model.py
@@ -855,37 +855,14 @@ class LLMASR4(nn.Module):
 
     def __init__(
         self,
-        specaug: str = None,
-        specaug_conf: dict = None,
-        normalize: str = None,
-        normalize_conf: dict = None,
         audio_encoder: str = None,
         audio_encoder_conf: dict = None,
         audio_adaptor: str = None,
         audio_adaptor_conf: dict = None,
-        decoder: str = None,
-        decoder_conf: dict = None,
-        ctc: str = None,
-        ctc_conf: dict = None,
-        ctc_weight: float = 0.5,
         llm: str = None,
         llm_conf: dict = None,
         input_size: int = 80,
-        vocab_size: int = -1,
-        ignore_id: int = -1,
-        blank_id: int = 0,
-        sos: int = 1,
-        eos: int = 2,
-        lsm_weight: float = 0.0,
         length_normalized_loss: bool = False,
-        report_cer: bool = True,
-        report_wer: bool = True,
-        sym_space: str = "<space>",
-        sym_blank: str = "<blank>",
-        # extract_feats_in_collect_stats: bool = True,
-        share_embedding: bool = False,
-        # preencoder: Optional[AbsPreEncoder] = None,
-        # postencoder: Optional[AbsPostEncoder] = None,
         **kwargs,
     ):
 
@@ -1005,12 +982,12 @@ class LLMASR4(nn.Module):
             batch_size_speech, frames, _ = speech.shape
             batch_size, token_num = input_ids.shape
 
-            with torch.cuda.amp.autocast(enabled=False):
-                # audio encoder
-                encoder_out, encoder_out_lens = self.encode(speech, speech_lengths)
+            # with torch.cuda.amp.autocast(enabled=False):
+            # audio encoder
+            encoder_out, encoder_out_lens = self.encode(speech, speech_lengths)
 
-                # audio_adaptor
-                encoder_out, encoder_out_lens = self.audio_adaptor(encoder_out, encoder_out_lens)
+            # audio_adaptor
+            encoder_out, encoder_out_lens = self.audio_adaptor(encoder_out, encoder_out_lens)
 
             batch_size, token_num, dims = inputs_embeds.shape
             fake_token_len = kwargs.get("fake_token_len")