  The base model therefore has a final sequence length that is a quarter of the original one. This model can be used
  directly for tasks that just require a sentence summary (like sequence classification or multiple choice). For other
  tasks, the full model is used; this full model has a decoder that upsamples the final hidden states to the same
  sequence length as the input.
The Funnel Transformer checkpoints are all available with a full version and a base version. The first ones should be
  used for [FunnelModel], [FunnelForPreTraining],
  [FunnelForMaskedLM], [FunnelForTokenClassification] and
  class:~transformers.FunnelForQuestionAnswering. The second ones should be used for
  [FunnelBaseModel], [FunnelForSequenceClassification] and
  [FunnelForMultipleChoice].
This model was contributed by sgugger. The original code can be found here.
