with the Perceiver. There are many more use cases, including question answering, named-entity recognition, object detection, 
audio classification, video classification, etc. 
Note:
Perceiver does not work with torch.nn.DataParallel due to a bug in PyTorch, see issue #36035
Perceiver specific outputs
[[autodoc]] models.perceiver.modeling_perceiver.PerceiverModelOutput
[[autodoc]] models.perceiver.modeling_perceiver.PerceiverDecoderOutput
[[autodoc]] models.perceiver.modeling_perceiver.PerceiverMaskedLMOutput
[[autodoc]] models.perceiver.modeling_perceiver.PerceiverClassifierOutput
PerceiverConfig
[[autodoc]] PerceiverConfig
PerceiverTokenizer
[[autodoc]] PerceiverTokenizer
    - call
PerceiverFeatureExtractor
[[autodoc]] PerceiverFeatureExtractor
    - call
PerceiverTextPreprocessor
[[autodoc]] models.perceiver.modeling_perceiver.PerceiverTextPreprocessor
