class_docstr: Filter samples based on text perplexity
  
  Example::
  
      sample 1: "I love textflint", score: 6.7
      sample 2: "I love TextFlinet", score: 6.34
code: def load_model(self):
      from transformers import GPT2Tokenizer, GPT2LMHeadModel
  
      self.tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
      self.model = GPT2LMHeadModel.from_pretrained("gpt2")
      self.model.to(self.device)
  
file_path: textflint/textflint/generation/subpopulation/UTCN/lm.py
imports: import torch
  import math
  from ..subpopulation import SubPopulation
label_desc: Use image node_id 3 for calling the LMSubPopulation obj's underlying member method code with example usage: obj.load_model() without return types