ValueError: Cannot merge LORA layers when the model is gptq quantized

[xiulidetangtang]

报错信息是这个 (IEPile) C:\Users\apoll\IEPile>predict.bat 07/10/2024 15:09:10 - INFO - main - model_class:<class 'transformers.models.auto.modeling_auto.AutoModelForCausalLM'> tokenizer_class:<class 'transformers.models.auto.tokenization_auto.AutoTokenizer'>

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. CUDA extension not installed. CUDA extension not installed. C:\anaconda\envs\IEPile\lib\site-packages\transformers\modeling_utils.py:4225: FutureWarning: _is_quantized_training_enabled is going to be deprecated in transformers 4.39.0. Please use model.hf_quantizer.is_trainable instead warnings.warn( Some weights of the model checkpoint at C:\Users\apoll\IEPile\models\qwen-0.5b were not used when initializing Qwen2ForCausalLM: ['model.layers.0.mlp.down_proj.bias', 'model.layers.0.mlp.gate_proj.bias', 'model.layers.0.mlp.up_proj.bias', 'model.layers.0.self_attn.o_proj.bias', 'model.layers.1.mlp.down_proj.bias', 'model.layers.1.mlp.gate_proj.bias', 'model.layers.1.mlp.up_proj.bias', 'model.layers.1.self_attn.o_proj.bias', 'model.layers.10.mlp.down_proj.bias', 'model.layers.10.mlp.gate_proj.bias', 'model.layers.10.mlp.up_proj.bias', 'model.layers.10.self_attn.o_proj.bias', 'model.layers.11.mlp.down_proj.bias', 'model.layers.11.mlp.gate_proj.bias', 'model.layers.11.mlp.up_proj.bias', 'model.layers.11.self_attn.o_proj.bias', 'model.layers.12.mlp.down_proj.bias', 'model.layers.12.mlp.gate_proj.bias', 'model.layers.12.mlp.up_proj.bias', 'model.layers.12.self_attn.o_proj.bias', 'model.layers.13.mlp.down_proj.bias', 'model.layers.13.mlp.gate_proj.bias', 'model.layers.13.mlp.up_proj.bias', 'model.layers.13.self_attn.o_proj.bias', 'model.layers.14.mlp.down_proj.bias', 'model.layers.14.mlp.gate_proj.bias', 'model.layers.14.mlp.up_proj.bias', 'model.layers.14.self_attn.o_proj.bias', 'model.layers.15.mlp.down_proj.bias', 'model.layers.15.mlp.gate_proj.bias', 'model.layers.15.mlp.up_proj.bias', 'model.layers.15.self_attn.o_proj.bias', 'model.layers.16.mlp.down_proj.bias', 'model.layers.16.mlp.gate_proj.bias', 'model.layers.16.mlp.up_proj.bias', 'model.layers.16.self_attn.o_proj.bias', 'model.layers.17.mlp.down_proj.bias', 'model.layers.17.mlp.gate_proj.bias', 'model.layers.17.mlp.up_proj.bias', 'model.layers.17.self_attn.o_proj.bias', 'model.layers.18.mlp.down_proj.bias', 'model.layers.18.mlp.gate_proj.bias', 'model.layers.18.mlp.up_proj.bias', 'model.layers.18.self_attn.o_proj.bias', 'model.layers.19.mlp.down_proj.bias', 'model.layers.19.mlp.gate_proj.bias', 'model.layers.19.mlp.up_proj.bias', 'model.layers.19.self_attn.o_proj.bias', 'model.layers.2.mlp.down_proj.bias', 'model.layers.2.mlp.gate_proj.bias', 'model.layers.2.mlp.up_proj.bias', 'model.layers.2.self_attn.o_proj.bias', 'model.layers.20.mlp.down_proj.bias', 'model.layers.20.mlp.gate_proj.bias', 'model.layers.20.mlp.up_proj.bias', 'model.layers.20.self_attn.o_proj.bias', 'model.layers.21.mlp.down_proj.bias', 'model.layers.21.mlp.gate_proj.bias', 'model.layers.21.mlp.up_proj.bias', 'model.layers.21.self_attn.o_proj.bias', 'model.layers.22.mlp.down_proj.bias', 'model.layers.22.mlp.gate_proj.bias', 'model.layers.22.mlp.up_proj.bias', 'model.layers.22.self_attn.o_proj.bias', 'model.layers.23.mlp.down_proj.bias', 'model.layers.23.mlp.gate_proj.bias', 'model.layers.23.mlp.up_proj.bias', 'model.layers.23.self_attn.o_proj.bias', 'model.layers.3.mlp.down_proj.bias', 'model.layers.3.mlp.gate_proj.bias', 'model.layers.3.mlp.up_proj.bias', 'model.layers.3.self_attn.o_proj.bias', 'model.layers.4.mlp.down_proj.bias', 'model.layers.4.mlp.gate_proj.bias', 'model.layers.4.mlp.up_proj.bias', 'model.layers.4.self_attn.o_proj.bias', 'model.layers.5.mlp.down_proj.bias', 'model.layers.5.mlp.gate_proj.bias', 'model.layers.5.mlp.up_proj.bias', 'model.layers.5.self_attn.o_proj.bias', 'model.layers.6.mlp.down_proj.bias', 'model.layers.6.mlp.gate_proj.bias', 'model.layers.6.mlp.up_proj.bias', 'model.layers.6.self_attn.o_proj.bias', 'model.layers.7.mlp.down_proj.bias', 'model.layers.7.mlp.gate_proj.bias', 'model.layers.7.mlp.up_proj.bias', 'model.layers.7.self_attn.o_proj.bias', 'model.layers.8.mlp.down_proj.bias', 'model.layers.8.mlp.gate_proj.bias', 'model.layers.8.mlp.up_proj.bias', 'model.layers.8.self_attn.o_proj.bias', 'model.layers.9.mlp.down_proj.bias', 'model.layers.9.mlp.gate_proj.bias', 'model.layers.9.mlp.up_proj.bias', 'model.layers.9.self_attn.o_proj.bias']

• This IS expected if you are initializing Qwen2ForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
• This IS NOT expected if you are initializing Qwen2ForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). 07/10/2024 15:09:11 - INFO - model.adapter - Fine-tuning method: LoRA Traceback (most recent call last): File "C:\Users\apoll\IEPile\src\inference.py", line 121, in main() File "C:\Users\apoll\IEPile\src\inference.py", line 115, in main inference(model_args, data_args, training_args, finetuning_args, generating_args, inference_args) File "C:\Users\apoll\IEPile\src\inference.py", line 47, in inference model, tokenizer = load_model_and_tokenizer( File "C:\Users\apoll\IEPile\src\model\loader.py", line 140, in load_model_and_tokenizer model = init_adapter(model, model_args, finetuning_args, is_trainable) File "C:\Users\apoll\IEPile\src\model\adapter.py", line 166, in init_adapter model = model.merge_and_unload() File "C:\anaconda\envs\IEPile\lib\site-packages\peft\tuners\lora\model.py", line 838, in merge_and_unload return self._unload_and_optionally_merge( File "C:\anaconda\envs\IEPile\lib\site-packages\peft\tuners\lora\model.py", line 445, in _unload_and_optionally_merge self._check_merge_allowed() File "C:\anaconda\envs\IEPile\lib\site-packages\peft\tuners\lora\model.py", line 423, in _check_merge_allowed raise ValueError("Cannot merge LORA layers when the model is gptq quantized") ValueError: Cannot merge LORA layers when the model is gptq quantized 请问该怎么解决，谢谢

[guihonghao]

https://github.com/hiyouga/LLaMA-Factory/issues/1545 参考这个issue，GPTQ 量化后的模型无法合并 LoRA，只能用原始未量化的模型。

[xiulidetangtang]

hiyouga/LLaMA-Factory#1545 参考这个issue，GPTQ 量化后的模型无法合并 LoRA，只能用原始未量化的模型。 感谢