class_docstr: Transformer backend wih Huggingface transformer models
class_docstr_tok: ["Transformer","backend","wih","Huggingface","transformer","models"]
docstr: Build the multimodal embeddings using the transformer base
  embeddings.
docstr_tok: ["Build","the","multimodal","embeddings","using","the","transformer","base","embeddings","."]
code: def build_embeddings(self):
      """Build the multimodal embeddings using the transformer base
      embeddings.
      """
      self.embeddings = HuggingfaceEmbeddings(
          self.config, self.transformer_config, self.transformer
      )
  
imports: from copy import deepcopy
  from typing import Any, Dict, List, Type
  import torch
  from mmf.common.registry import registry
  from mmf.models.transformers.base import BaseTransformer, BaseTransformerBackend
  from mmf.modules.hf_layers import BertModelJit, replace_with_jit
  from omegaconf import OmegaConf
  from torch import nn, Tensor
label_desc: Use image node_id 4 for calling the HuggingfaceBackend obj's underlying member method code with example usage: obj.build_embeddings() without return types