code: def msillm_quality_3(pretrained=True, **kwargs):
      r"""
      Pretrained MS-ILLM model
  
      This model was trained for the paper:
  
      MJ Muckley, A El-Nouby, K Ullrich, H Jegou, J Verbeek.
      Improving Statistical Fidelity for Neural Image Compression with Implicit
      Local Likelihood Models. In *ICML*, 2023.
  
      The target bitrate is 0.14 bits per pixel
  
      The pretrained weights are released under the CC-BY-NC 4.0 license
      available at
      https://github.com/facebookresearch/NeuralCompression/blob/main/WEIGHTS_LICENSE
  
      pretrained (bool): kwargs, load pretrained weights into the model
      """
  
      return _msillm_quality_3(pretrained=pretrained, **kwargs)
  
imports: from neuralcompression.zoo import msillm_quality_1
  from neuralcompression.zoo import msillm_quality_2
  from neuralcompression.zoo import msillm_quality_3
  from neuralcompression.zoo import msillm_quality_4
  from neuralcompression.zoo import msillm_quality_5
  from neuralcompression.zoo import msillm_quality_6
  from neuralcompression.zoo import noganms_quality_1
  from neuralcompression.zoo import noganms_quality_2
  from neuralcompression.zoo import noganms_quality_3
  from neuralcompression.zoo import noganms_quality_4
  from neuralcompression.zoo import noganms_quality_5
  from neuralcompression.zoo import noganms_quality_6
  from neuralcompression.zoo import vqvae_xcit_p8_ch64_cb1024_h8
label_desc: Use image node_id 3 for calling a global function with example usage: msillm_quality_3(pretrained) and returns: _msillm_quality_3