A library that handles everything with 🤗 and supports batching to models in PORORO
Project description
DOOLY 🦕
PORORO에는 아래 세 가지 단점이 존재합니다.
- 일부 task의 batch화 불가능
- 내부 tokenize 과정 및 모듈 구조 확인이 어려움
- fairseq dependency
Dooly는 위 단점 세 가지를 개선한 라이브러리입니다.
- 모든 task를 batch화하여 inference 가능
- task별 tokenizer, model을 모듈로 분리하여 출력값 확인 가능
- 모든 것을 huggingface transformers로 처리
How to use?
아래와 같이 간단하게 사용 가능합니다
- install
$ pip install dooly
- how to use
- PORORO와 동일하게 사용할 수 있습니다.
from dooly import Dooly
ner = Dooly(task="ner", lang="ko")
Supported Tasks
- Back Translation Data Augmentation
- Dependency Parsing
- Machine Reading Comprehension
- Machine Translation
- Named Entity Recognition
- Natural Language Inference
- Pos Tagging
- Question Generation
- Word Embedding
- Word Sense Disambiguation
- Zero Shot Topic Classification
Citations
@misc{pororo,
author = {Heo, Hoon and Ko, Hyunwoong and Kim, Soohwan and
Han, Gunsoo and Park, Jiwoo and Park, Kyubyong},
title = {PORORO: Platform Of neuRal mOdels for natuRal language prOcessing},
howpublished = {\url{https://github.com/kakaobrain/pororo}},
year = {2021},
}
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