File size: 2,210 Bytes
57b0bdd 1e3ebac 57b0bdd bbf42c3 57b0bdd 73a21c8 1e3ebac 73a21c8 0a587ab 73a21c8 1e3ebac 667af5a 1e3ebac 667af5a 1e3ebac 49a967d 1e3ebac 49a967d 1e3ebac 49a967d 1e3ebac 49a967d 1e3ebac 49a967d 1e3ebac 49a967d 3a93017 7ef3f9c 3a93017 667af5a 1e3ebac 667af5a 1e3ebac |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
language: en
license: mit
tags:
- layoutlm
- document-question-answering
- pdf
---
# 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 AutoTokenizer, pipeline
tokenizer = AutoTokenizer.from_pretrained(
"impira/layoutlm-document-qa",
add_prefix_space=True,
)
nlp = pipeline(
model="impira/layoutlm-document-qa",
tokenizer=tokenizer,
trust_remote_code=True,
)
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 was recently landed in transformers via [PR #18407](https://github.com/huggingface/transformers/pull/18407), so you'll need to use a recent version of transformers, for example:
```bash
pip install git+https://github.com/huggingface/transformers.git@5c4c869014f5839d04c1fd28133045df0c91fd84
```
The pipeline is currently in review ([PR #18414](https://github.com/huggingface/transformers/pull/18414)). In the meantime, you'll have to use the `trust_remote_code=True` flag to run it.
## About us
This model was created by the team at [Impira](https://www.impira.com/).
|