baichuan2-7B-Chat awq fuse_layer=True error

[feipengheart]

root@localhost:/opt/AI# CUDA_VISIBLE_DEVICES=3 python Baichuan2/awq_chat.py
Xformers is not installed correctly. If you want to use memory_efficient_attention to accelerate training use the following command to install Xformers
pip install xformers.
Replacing layers...: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 32/32 [00:02<00:00, 10.70it/s]
Fusing layers...: 0%| | 0/32 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/opt/AI/Baichuan2/awq_chat.py", line 7, in
model = AutoAWQForCausalLM.from_quantized(quant_path, fuse_layers=True)
File "/usr/local/lib/python3.9/site-packages/awq/models/auto.py", line 94, in from_quantized
return AWQ_CAUSAL_LM_MODEL_MAP[model_type].from_quantized(
File "/usr/local/lib/python3.9/site-packages/awq/models/base.py", line 434, in from_quantized
self.fuse_layers(model)
File "/usr/local/lib/python3.9/site-packages/awq/models/baichuan.py", line 19, in fuse_layers
fuser.fuse_transformer()
File "/usr/local/lib/python3.9/site-packages/awq/models/baichuan.py", line 113, in fuse_transformer
module.input_layernorm.weight, module.input_layernorm.epsilon
File "/usr/local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1709, in getattr
raise AttributeError(f"'{type(self).name}' object has no attribute '{name}'")
AttributeError: 'RMSNorm' object has no attribute 'epsilon'

inference code:
from awq import AutoAWQForCausalLM
from transformers import AutoTokenizer, TextStreamer

quant_path = "/opt/AI/models/Baichuan2-7B-Chat-awq"

Load model

model = AutoAWQForCausalLM.from_quantized(quant_path, fuse_layers=True)
tokenizer = AutoTokenizer.from_pretrained(quant_path, trust_remote_code=True)
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
print(model)

prompt_template = "<reserved_106>{prompt}<reserved_107>"

prompt = "You're standing on the surface of the Earth. "
"You walk one mile south, one mile west and one mile north. "
"You end up exactly where you started. Where are you?"