code: def init_adapters(self, model_config, adapters_config):
      # Wrap layers for LoRA
      self.mlp.down_proj = LoRALinear.wrap(
          self.mlp.down_proj,
          "intermediate",
          model_config,
          adapters_config,
      )
      self.mlp.up_proj = LoRALinear.wrap(
          self.mlp.up_proj, "output", model_config, adapters_config
      )
  
      self.attention_adapters = BottleneckLayer("mh_adapter")
      self.output_adapters = BottleneckLayer("output_adapter")
  
file_path: adapters/src/adapters/models/llama/mixin_llama.py
imports: from typing import Iterable, Tuple
  import torch.nn
  from ...methods.bottleneck import BottleneckLayer
  from ...methods.lora import LoRALinear
  from ...methods.prefix_tuning import PrefixTuningLayer
  from ...model_mixin import EmbeddingAdaptersMixin, InvertibleAdaptersMixin, ModelBaseAdaptersMixin
label_desc: Use image node_id 1 for calling the LlamaDecoderLayerMixin obj's underlying member method code with example usage: obj.init_adapters(model_config, adapters_config) without return types