runtime error

Exit code: 1. Reason: ue to insufficient memory: - cpu: 989349888 bytes required These minimum requirements are specific to this allocation attempt and may vary. Consider increasing the available memory for these devices to at least the specified minimum, or adjusting the model config. Loading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s] Loading checkpoint shards: 100%|██████████| 2/2 [00:00<00:00, 34807.50it/s] generation_config.json: 0%| | 0.00/180 [00:00<?, ?B/s] generation_config.json: 100%|██████████| 180/180 [00:00<00:00, 1.17MB/s] ERROR:__main__:Error loading model or tokenizer: You are trying to offload the whole model to the disk. Please use the `disk_offload` function instead. Traceback (most recent call last): File "/app/app.py", line 18, in <module> model = AutoModelForCausalLM.from_pretrained( MODEL_NAME, ...<2 lines>... low_cpu_mem_usage=True ) File "/usr/local/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 604, in from_pretrained return model_class.from_pretrained( ~~~~~~~~~~~~~~~~~~~~~~~~~~~^ pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ) ^ File "/usr/local/lib/python3.13/site-packages/transformers/modeling_utils.py", line 277, in _wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.13/site-packages/transformers/modeling_utils.py", line 5140, in from_pretrained dispatch_model(model, **device_map_kwargs) ~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.13/site-packages/accelerate/big_modeling.py", line 504, in dispatch_model raise ValueError( "You are trying to offload the whole model to the disk. Please use the `disk_offload` function instead." ) ValueError: You are trying to offload the whole model to the disk. Please use the `disk_offload` function instead.

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