runtime error

��█████████| 1.95G/1.95G [00:36<00:00, 46.3MB/s] Downloading (…)l-00002-of-00002.bin: 100%|██████████| 1.95G/1.95G [00:36<00:00, 54.0MB/s] Downloading shards: 100%|██████████| 2/2 [03:27<00:00, 91.76s/it] Downloading shards: 100%|██████████| 2/2 [03:27<00:00, 103.63s/it] ===================================BUG REPORT=================================== Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues ================================================================================ /home/user/.local/lib/python3.8/site-packages/bitsandbytes/cextension.py:31: UserWarning: The installed version of bitsandbytes was compiled without GPU support. 8-bit optimizers and GPU quantization are unavailable. warn("The installed version of bitsandbytes was compiled without GPU support. " Traceback (most recent call last): File "app.py", line 13, in <module> model = AutoModelForSeq2SeqLM.from_pretrained(model_id, load_in_8bit=True, device_map="auto") File "/home/user/.local/lib/python3.8/site-packages/transformers/models/auto/auto_factory.py", line 468, in from_pretrained return model_class.from_pretrained( File "/home/user/.local/lib/python3.8/site-packages/transformers/modeling_utils.py", line 2740, 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.

Container logs: