code: def __init__(self, config: VipLlavaConfig):
      super().__init__(config)
      self.vision_tower = AutoModel.from_config(config.vision_config)
  
      self.multi_modal_projector = VipLlavaMultiModalProjector(config)
      self.vocab_size = config.vocab_size
      self.language_model = AutoModelForCausalLM.from_config(
          config.text_config,
          attn_implementation=config._attn_implementation,
      )
      self.pad_token_id = (
          self.config.pad_token_id
          if self.config.pad_token_id is not None
          else -1
      )
      self.post_init()
  
imports: from dataclasses import dataclass
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from ...None import PreTrainedModel
  from ...activations import ACT2FN
  from ...cache_utils import Cache
  from ...modeling_outputs import ModelOutput
  from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from ..auto import AutoModel, AutoModelForCausalLM
  from .configuration_vipllava import VipLlavaConfig
label_desc: Use image node_id 1 to create a new VipLlavaForConditionalGeneration object from inherited base classes: VipLlavaPreTrainedModel with example: obj = VipLlavaForConditionalGeneration(config)