class_docstr: This class initializes the linear head to zeros
code: def __init__(self, name, linear_probe=False, **kwargs):
      config = AutoConfig.from_pretrained(name, **kwargs)
      super().__init__(config)
      self.num_labels = config.num_labels
      lm = AutoModelForCausalLM.from_pretrained(name, **kwargs)
      self.lm = lm
      self.transformer = lm.transformer
      hidden_size = getattr(
          config, "n_embd", getattr(config, "hidden_size", None)
      )
      self.score = torch.nn.Linear(
          hidden_size, self.num_labels, bias=False
      ).to(lm.lm_head.weight.dtype)
      torch.nn.init.normal_(self.score.weight, std=0.0)
      self.linear_probe = linear_probe
  
file_path: weak-to-strong/weak_to_strong/model.py
imports: from dataclasses import dataclass
  import torch
  from transformers import AutoConfig, AutoModelForCausalLM, PreTrainedModel
label_desc: Use image node_id 1 to create a new TransformerWithHead object from inherited base classes: PreTrainedModel with example: obj = TransformerWithHead(name, linear_probe)