code: def __init__(self, config, weights):
      super().__init__()
  
      self.model = FlashLlamaModel(config, weights)
      self.lm_head = TensorParallelHead.load(
          config,
          prefix="lm_head",
          weights=weights,
      )
  
imports: import torch
  import torch.distributed
  from torch import nn
  from transformers.activations import ACT2FN
  from transformers.configuration_utils import PretrainedConfig
  from typing import Optional, List, Tuple
  from text_generation_server.utils import paged_attention, flash_attn
  from text_generation_server.utils.layers import TensorParallelRowLinear, TensorParallelColumnLinear, TensorParallelEmbedding, PositionRotaryEmbedding, TensorParallelHead, get_linear, FastRMSNorm
label_desc: Use image node_id 1 to create a new FlashLlamaForCausalLM object from inherited base classes: torch.nn with example: obj = FlashLlamaForCausalLM(config, weights)