code: def __init__(self, config):
      super().__init__(config)
      self.model = LlamaModel(config)
      init(self.model)
  
      self._init_head_modules()
  
      self.init_weights()
  
      # Model parallel
      self.model_parallel = False
      self.device_map = None
      self.post_init()
  
file_path: adapters/src/adapters/models/llama/adapter_model.py
imports: import logging
  import torch
  from transformers.models.llama.modeling_llama import LLAMA_START_DOCSTRING, LlamaModel, LlamaPreTrainedModel
  from transformers.utils import add_start_docstrings
  from ...composition import adjust_tensors_for_parallel
  from ...heads import CausalLMHead, ClassificationHead, ModelWithFlexibleHeadsAdaptersMixin, MultiLabelClassificationHead, TaggingHead
  from ...model_mixin import EmbeddingAdaptersWrapperMixin
  from ...wrappers import init
label_desc: Use image node_id 1 to create a new LlamaAdapterModel object from inherited base classes: EmbeddingAdaptersWrapperMixin, ModelWithFlexibleHeadsAdaptersMixin, LlamaPreTrainedModel with example: obj = LlamaAdapterModel(config)