code: def hub_models(cls):
      return {
          "roberta.base": "http://dl.fbaipublicfiles.com/fairseq/models/roberta.base.tar.gz",
          "roberta.large": "http://dl.fbaipublicfiles.com/fairseq/models/roberta.large.tar.gz",
          "roberta.large.mnli": "http://dl.fbaipublicfiles.com/fairseq/models/roberta.large.mnli.tar.gz",
          "roberta.large.wsc": "http://dl.fbaipublicfiles.com/fairseq/models/roberta.large.wsc.tar.gz",
      }
  
imports: import logging
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq import utils
  from fairseq.models import FairseqEncoder, FairseqEncoderModel, register_model, register_model_architecture
  from fairseq.models.transformer import DEFAULT_MIN_PARAMS_TO_WRAP, TransformerEncoder
  from fairseq.modules import LayerNorm
  from fairseq.modules.quant_noise import quant_noise
  from fairseq.modules.transformer_sentence_encoder import init_bert_params
  from fairseq.utils import safe_getattr, safe_hasattr
  from .hub_interface import RobertaHubInterface
label_desc: Use image node_id 1 for calling the RobertaModel obj's underlying member method code with example usage: obj.hub_models(cls) and returns: dict