runtime error

Exit code: 1. Reason: sign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?) module._load_from_state_dict( /usr/local/lib/python3.12/site-packages/torch/nn/modules/module.py:2589: UserWarning: for base_model.model.model.layers.31.self_attn.v_proj.lora_A.default.weight: 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?) module._load_from_state_dict( /usr/local/lib/python3.12/site-packages/torch/nn/modules/module.py:2589: UserWarning: for base_model.model.model.layers.31.self_attn.v_proj.lora_B.default.weight: 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?) module._load_from_state_dict( Traceback (most recent call last): File "/app/app.py", line 9, in <module> model, tokenizer = load_model(use_finetuned=True) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/app/pipeline.py", line 174, in load_model model = PeftModel.from_pretrained(base_model, FINETUNED_DIR) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/peft/peft_model.py", line 568, in from_pretrained load_result = model.load_adapter( ^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/peft/peft_model.py", line 1427, in load_adapter self._update_offload(offload_index, adapters_weights) File "/usr/local/lib/python3.12/site-packages/peft/peft_model.py", line 1236, in _update_offload safe_module = dict(self.named_modules())[extended_prefix] ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ KeyError: 'base_model.model.model.model.embed_tokens'

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