document-level pretraining. It achieves new state-of-the-art results in several downstream tasks, including form
understanding (from 70.72 to 79.27), receipt understanding (from 94.02 to 95.24) and document image classification
(from 93.07 to 94.42).
Tips:
In addition to input_ids, [~transformers.LayoutLMModel.forward] also expects the input bbox, which are
  the bounding boxes (i.e. 2D-positions) of the input tokens. These can be obtained using an external OCR engine such
  as Google's Tesseract (there's a Python wrapper available). Each bounding box should be in (x0, y0, x1, y1) format, where
  (x0, y0) corresponds to the position of the upper left corner in the bounding box, and (x1, y1) represents the
  position of the lower right corner. Note that one first needs to normalize the bounding boxes to be on a 0-1000
