readme: ---
  language: en
  license: mit
  pipeline_tag: document-question-answering
  tags:
   - layoutlm
   - document-question-answering
   - pdf
  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 Visual Question Answering
  
  This is a fine-tuned version of the multi-modal [LayoutLM](https://aka.ms/layoutlm) model for the task of question answering on documents. It has been fine-tuned using both the [SQuAD2.0](https://huggingface.co/datasets/squad_v2) and [DocVQA](https://www.docvqa.org/) datasets.
  
  ## Getting started with the model
  
  To run these examples, you must have [PIL](https://pillow.readthedocs.io/en/stable/installation.html), [pytesseract](https://pypi.org/project/pytesseract/), and [PyTorch](https://pytorch.org/get-started/locally/) installed in addition to [transformers](https://huggingface.co/docs/transformers/index).
  
  ```python
  from transformers import pipeline
  
  nlp = pipeline(
      "document-question-answering",
      model="impira/layoutlm-document-qa",
  )
  
  nlp(
      "https://templates.invoicehome.com/invoice-template-us-neat-750px.png",
      "What is the invoice number?"
  )
  # {'score': 0.9943977, 'answer': 'us-001', 'start': 15, 'end': 15}
  
  nlp(
      "https://miro.medium.com/max/787/1*iECQRIiOGTmEFLdWkVIH2g.jpeg",
      "What is the purchase amount?"
  )
  # {'score': 0.9912159, 'answer': '$1,000,000,000', 'start': 97, 'end': 97}
  
  nlp(
      "https://www.accountingcoach.com/wp-content/uploads/2013/10/income-statement-example@2x.png",
      "What are the 2020 net sales?"
  )
  # {'score': 0.59147286, 'answer': '$ 3,750', 'start': 19, 'end': 20}
  ```
  
  **NOTE**: This model and pipeline was recently landed in transformers via [PR #18407](https://github.com/huggingface/transformers/pull/18407) and [PR #18414](https://github.com/huggingface/transformers/pull/18414), so you'll need to use a recent version of transformers, for example:
  
  ```bash
  pip install git+https://github.com/huggingface/transformers.git@2ef774211733f0acf8d3415f9284c49ef219e991
  ```
  
  ## About us
  
  This model was created by the team at [Impira](https://www.impira.com/).
  