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layoutlm-invoices

Document Question Answering
Transformers
PyTorch
English
layoutlm
pdf
invoices
Inference Endpoints
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layoutlm-invoices / README.md
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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

Broken Address

After

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.