chunk_content: First element of model_output contains all token embeddings
          input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
          return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
  
      def __getattr__(self, name: str):
          """Forward missing attributes to the wrapped module."""
          try:
              return super().__getattr__(name)  # defer