runtime error

_model.model.lm_head.modules_to_save.default.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?) warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta ' Traceback (most recent call last): File "/home/user/app/app.py", line 44, in <module> ft_model = PeftModel.from_pretrained(model, "yurezsml/phi2_chan", offload_dir="./") File "/home/user/.local/lib/python3.10/site-packages/peft/peft_model.py", line 353, in from_pretrained model.load_adapter(model_id, adapter_name, is_trainable=is_trainable, **kwargs) File "/home/user/.local/lib/python3.10/site-packages/peft/peft_model.py", line 727, in load_adapter dispatch_model( File "/home/user/.local/lib/python3.10/site-packages/accelerate/big_modeling.py", line 374, in dispatch_model raise ValueError( ValueError: We need an `offload_dir` to dispatch this model according to this `device_map`, the following submodules need to be offloaded: base_model.model.model.layers.8, base_model.model.model.layers.9, base_model.model.model.layers.10, base_model.model.model.layers.11, base_model.model.model.layers.12, base_model.model.model.layers.13, base_model.model.model.layers.14, base_model.model.model.layers.15, base_model.model.model.layers.16, base_model.model.model.layers.17, base_model.model.model.layers.18, base_model.model.model.layers.19, base_model.model.model.layers.20, base_model.model.model.layers.21, base_model.model.model.layers.22, base_model.model.model.layers.23, base_model.model.model.layers.24, base_model.model.model.layers.25, base_model.model.model.layers.26, base_model.model.model.layers.27, base_model.model.model.layers.28, base_model.model.model.layers.29, base_model.model.model.layers.30, base_model.model.model.layers.31, base_model.model.model.final_layernorm, base_model.model.lm_head.

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