Edit model card

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:


Broken Address


However this model is able to predict non-consecutive tokens and therefore the address correctly:

Two-line Address

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.

Downloads last month
Hosted inference API
Document Question Answering
Drag image file here or click to browse from your device
This model can be loaded on the Inference API on-demand.

Spaces using impira/layoutlm-invoices 14