need to set `load_in_8bit_fp32_cpu_offload=True` and pass a custom `device_map` to `from_pretrained`.

[SeekPoint]

(gh_qlora-chinese-LLM) ub2004@ub2004-B85M-A0:~/llm_dev/qlora-chinese-LLM$ python3 qlora.py --model_name="chatglm" --model_name_or_path="/data-ssd-1t/hf_model/chatglm-6b" --trust_remote_code=True --dataset="msra" --source_max_len=128 --target_max_len=64 --do_train --save_total_limit=1 --padding_side="left" --per_device_train_batch_size=8 --do_eval --bits=4 --save_steps=10 --gradient_accumulation_steps=1 --learning_rate=1e-5 --output_dir="./output/chatglm-6b/" --lora_r=8 --lora_alpha=32

===================================BUG REPORT=================================== Welcome to bitsandbytes. For bug reports, please run

python -m bitsandbytes

and submit this information together with your error trace to: https://github.com/TimDettmers/bitsandbytes/issues

bin /home/ub2004/anaconda3/envs/gh_qlora-chinese-LLM/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cpu.so /home/ub2004/anaconda3/envs/gh_qlora-chinese-LLM/lib/python3.10/site-packages/bitsandbytes/cextension.py:34: UserWarning: The installed version of bitsandbytes was compiled without GPU support. 8-bit optimizers, 8-bit multiplication, and GPU quantization are unavailable. warn("The installed version of bitsandbytes was compiled without GPU support. " /home/ub2004/anaconda3/envs/gh_qlora-chinese-LLM/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cpu.so: undefined symbol: cadam32bit_grad_fp32 CUDA SETUP: Loading binary /home/ub2004/anaconda3/envs/gh_qlora-chinese-LLM/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cpu.so... loading base model /data-ssd-1t/hf_model/chatglm-6b... Traceback (most recent call last): File "/home/ub2004/llm_dev/qlora-chinese-LLM/qlora.py", line 1011, in train() File "/home/ub2004/llm_dev/qlora-chinese-LLM/qlora.py", line 836, in train model = get_accelerate_model(args, checkpoint_dir) File "/home/ub2004/llm_dev/qlora-chinese-LLM/qlora.py", line 375, in get_accelerate_model model = model_class[args.model_name].from_pretrained( File "/home/ub2004/llm_dev/qlora-chinese-LLM/transformers/src/transformers/models/auto/auto_factory.py", line 479, in from_pretrained return model_class.from_pretrained( File "/home/ub2004/llm_dev/qlora-chinese-LLM/transformers/src/transformers/modeling_utils.py", line 2819, in from_pretrained raise ValueError( ValueError: Some modules are dispatched on the CPU or the disk. Make sure you have enough GPU RAM to fit the quantized model. If you want to dispatch the model on the CPU or the disk while keeping these modules in 32-bit, you need to set load_in_8bit_fp32_cpu_offload=True and pass a custom device_map to from_pretrained. Check https://huggingface.co/docs/transformers/main/en/main_classes/quantization#offload-between-cpu-and-gpu for more details.

(gh_qlora-chinese-LLM) ub2004@ub2004-B85M-A0:~/llm_dev/qlora-chinese-LLM$