python train_reward_model.py failed

[SeekPoint]

(gh_Vicuna-LoRA-RLHF-PyTorch) amd00@asus00:~/llm_dev/Vicuna-LoRA-RLHF-PyTorch$ python train_reward_model.py --model_name './weights/vicuna-7b' --gradient_accumulation_steps 32 --per_device_train_batch_size 1 --train_subset 100 --eval_subset 10 --local_rank 0 --bf16 False

===================================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/amd00/anaconda3/envs/gh_Vicuna-LoRA-RLHF-PyTorch/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cpu.so
/home/amd00/anaconda3/envs/gh_Vicuna-LoRA-RLHF-PyTorch/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/amd00/anaconda3/envs/gh_Vicuna-LoRA-RLHF-PyTorch/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cpu.so: undefined symbol: cadam32bit_grad_fp32
CUDA SETUP: Loading binary /home/amd00/anaconda3/envs/gh_Vicuna-LoRA-RLHF-PyTorch/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cpu.so...
dataset_name: ./datasets/
device_map: auto
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /home/amd00/llm_dev/Vicuna-LoRA-RLHF-PyTorch/train_reward_model.py:172 in │
│ │
│ 169 # ) │
│ 170 │
│ 171 if "llama" in script_args.model_name or "vicuna" in script_args.model_name or "Vicuna" i │
│ ❱ 172 │ model = LlamaForSequenceClassification.from_pretrained( │
│ 173 │ │ script_args.model_name, │
│ 174 │ │ num_labels=1, │
│ 175 │ │ load_in_8bit=True, │
│ │
│ /home/amd00/.local/lib/python3.10/site-packages/transformers/modeling_utils.py:2740 in │
│ from_pretrained │
│ │
│ 2737 │ │ │ │ │ key: device_map[key] for key in device_map.keys() if key not in modu │
│ 2738 │ │ │ │ } │
│ 2739 │ │ │ │ if "cpu" in device_map_without_lm_head.values() or "disk" in device_map_ │
│ ❱ 2740 │ │ │ │ │ raise ValueError( │
│ 2741 │ │ │ │ │ │ """ │
│ 2742 │ │ │ │ │ │ Some modules are dispatched on the CPU or the disk. Make sure yo │
│ 2743 │ │ │ │ │ │ the quantized model. If you want to dispatch the model on the CP │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
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_Vicuna-LoRA-RLHF-PyTorch) amd00@asus00:~/llm_dev/Vicuna-LoRA-RLHF-PyTorch$