code: def __init__(self, config, weights):
      super().__init__(config)
      self.gpt_neox = FlashGPTNeoXModel(config, weights)
  
      self.embed_out = TensorParallelHead.load(
          config, prefix="embed_out", weights=weights
      )
  
imports: import torch
  import torch.distributed
  from torch import nn
  from transformers.activations import ACT2FN
  from transformers.modeling_utils import PreTrainedModel
  from transformers.models.gpt_neox import GPTNeoXConfig
  from typing import Optional, List, Tuple
  from text_generation_server.utils import paged_attention, flash_attn
  from text_generation_server.utils.flash_attn import attention
  from text_generation_server.utils.layers import TensorParallelRowLinear, TensorParallelColumnLinear, TensorParallelEmbedding, TensorParallelHead, FastLayerNorm, PositionRotaryEmbedding, get_linear
label_desc: Use image node_id 1 to create a new FlashGPTNeoXForCausalLM object from inherited base classes: FlashGPTNeoXPreTrainedModel with example: obj = FlashGPTNeoXForCausalLM(config, weights)