Error during inference LLaMA2 + LoRA: RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != float

[WJMacro]

Reminder

• [X] I have read the README and searched the existing issues.

System Info

Traceback (most recent call last):                                                                                                                                          
  File "[My_env_dir]/lib/python3.9/threading.py", line 980, in _bootstrap_inner                                                                        
    self.run()                                                                                                                                                              
  File "[My_env_dir]/lib/python3.9/threading.py", line 917, in run                                                                                     
    self._target(*self._args, **self._kwargs)                                                                                                                               
  File "[My_env_dir]/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context                                            
    return func(*args, **kwargs)                                                                                                                                            
  File "[My_env_dir]/lib/python3.9/site-packages/transformers/generation/utils.py", line 1758, in generate 
   result = self._sample(                                                                                                                                         [59/1930]
  File "[My_env_dir]/lib/python3.9/site-packages/transformers/generation/utils.py", line 2397, in _sample                                              
    outputs = self(                                                                                                                                                         
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl                                         
    return self._call_impl(*args, **kwargs)                                                                                                                                 
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl                                                 
    return forward_call(*args, **kwargs)                                                                                                                                    
  File "[My_env_dir]/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 1164, in forward                                   
    outputs = self.model(                                                                                                                                                   
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl                                         
    return self._call_impl(*args, **kwargs)                                                                                                                                 
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl                                                 
    return forward_call(*args, **kwargs)                                                                                                                                    
  File "[My_env_dir]/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 968, in forward                                    
    layer_outputs = decoder_layer(                                                                                                                                          
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl                                         
    return self._call_impl(*args, **kwargs)                                                                                                                                  
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl                                                 
    return forward_call(*args, **kwargs)                                                                                                                                    
  File "[My_env_dir]/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 713, in forward                                    
    hidden_states, self_attn_weights, present_key_value = self.self_attn(                                                                                                   
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl                                         
    return self._call_impl(*args, **kwargs)                                                                                                                                 
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl                                                 
    return forward_call(*args, **kwargs)                                                                                                                                    
  File "[My_env_dir]/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 616, in forward                                    
    key_states = self.k_proj(hidden_states)                                                                                                                                 
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl                                         
    return self._call_impl(*args, **kwargs)                                                                                                                                 
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl                                                 
    return forward_call(*args, **kwargs)                                                                                                                                    
  File "[My_env_dir]/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 116, in forward                                                     
    return F.linear(input, self.weight, self.bias)                                                                                                                          
RuntimeError: expected mat1 and mat2 to have the same dtype, but got: c10::Half != float

Reproduction

Inference config file:

model_name_or_path: llama2-7b-chat-hf 
template: llama2 
adapter_name_or_path: [LoRA path]
finetuning_type: lora

Run with LLaMA-Factory

llamafactory-cli chat config.yaml

Expected behavior

No response

Others

No response

[WJMacro]

Is it due to inconsistent precision of lora parameters?