naver-clova-ocr/bros-base-uncased

feature extractiontransformerstransformerspytorchbrosfeature-extractionarxiv:2108.04539endpoints_compatible
198.8K

BROS

GitHub: https://github.com/clovaai/bros

Introduction

BROS (BERT Relying On Spatiality) is a pre-trained language model focusing on text and layout for better key information extraction from documents.
Given the OCR results of the document image, which are text and bounding box pairs, it can perform various key information extraction tasks, such as extracting an ordered item list from receipts.
For more details, please refer to our paper:

BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from Documents
Teakgyu Hong, Donghyun Kim, Mingi Ji, Wonseok Hwang, Daehyun Nam, Sungrae Park
AAAI 2022 - Main Technical Track

[arXiv]

Pre-trained models

name# paramsHugging Face - Models
bros-base-uncased (this)< 110Mnaver-clova-ocr/bros-base-uncased
bros-large-uncased< 340Mnaver-clova-ocr/bros-large-uncased
DEPLOY IN 60 SECONDS

Run bros-base-uncased on Runcrate

Deploy on H100, A100, or RTX GPUs. Pay only for what you use. No setup required.