

The quickest way to get started with TrOCR is by checking the tutorial
  notebooks, which show how to use the model
  at inference time as well as fine-tuning on custom data.
TrOCR is pre-trained in 2 stages before being fine-tuned on downstream datasets. It achieves state-of-the-art results
  on both printed (e.g. the SROIE dataset and handwritten (e.g. the IAM
  Handwriting dataset text recognition tasks. For more
  information, see the official models.
TrOCR is always used within the VisionEncoderDecoder framework.