runtime error

, 21.9MB/s] pytorch_model-00002-of-00002.bin: 100%|█████████▉| 3.49G/3.50G [02:07<00:00, 20.2MB/s] pytorch_model-00002-of-00002.bin: 100%|██████████| 3.50G/3.50G [02:07<00:00, 22.3MB/s] pytorch_model-00002-of-00002.bin: 100%|██████████| 3.50G/3.50G [02:07<00:00, 27.5MB/s] Downloading shards: 100%|██████████| 2/2 [07:20<00:00, 204.04s/it] Downloading shards: 100%|██████████| 2/2 [07:20<00:00, 220.40s/it] /home/user/.local/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. /home/user/.local/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cpu.so: undefined symbol: cadam32bit_grad_fp32 warn("The installed version of bitsandbytes was compiled without GPU support. " Traceback (most recent call last): File "/home/user/app/app.py", line 19, in <module> model = transformers.AutoModelForCausalLM.from_pretrained( File "/home/user/.local/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py", line 484, in from_pretrained return model_class.from_pretrained( File "/home/user/.local/lib/python3.10/site-packages/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.

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