metadata
language: en
license: cc-by-nc-sa-4.0
pipeline_tag: document-question-answering
tags:
- layoutlm
- document-question-answering
- pdf
- invoices
widget:
- text: What is the invoice number?
src: >-
https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png
- text: What is the purchase amount?
src: >-
https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/contract.jpeg
LayoutLM for Invoices
This is a fine-tuned version of the multi-modal LayoutLM model for the task of question answering on invoices and other documents. It has been fine-tuned on a proprietary dataset of invoices as well as both SQuAD2.0 and DocVQA for general comprehension.
Non-consecutive tokens
Unlike other QA models, which can only extract consecutive tokens (because they predict the start and end of a sequence), this model can predict longer-range, non-consecutive sequences with an additional classifier head. For example, QA models often encounter this failure mode:
Before
After
However this model is able to predict non-consecutive tokens and therefore the address correctly:
Getting started with the model
The best way to use this model is via DocQuery.
About us
This model was created by the team at Impira.