code: def load(cls, config, prefix: str, weights, bias: bool):
      weight = weights.get_tensor(f"{prefix}.weight")
      if bias:
          bias = weights.get_tensor(f"{prefix}.bias")
      else:
          bias = None
      return cls(weight, bias)
  
imports: import os
  import torch
  import torch.distributed
  from torch import nn
  from torch.nn import functional
  from typing import List
  from loguru import logger
  from functools import lru_cache
  from accelerate import init_empty_weights
  from text_generation_server.utils.gptq.quant_linear import QuantLinear
  from text_generation_server.utils.import_utils import IS_CUDA_SYSTEM, IS_ROCM_SYSTEM
  from text_generation_server.utils.log import log_once
label_desc: Use image node_id 2 for calling the FastLinear obj's underlying member method code with example usage: obj.load(cls, config, prefix, weights, bias) and returns: cls