LanguageFlow

⚠️ WARNING

⚠️ This project is archived and no longer maintained ⚠️

⏩ From underthesea v1.2.0 , languageflow is merged with underthesea. So enjoy a better underthesea without languageflow dependency.

⚰️ RIP Languageflow

Old Readme

Data loaders and abstractions for text and NLP

Requirements

Install dependencies

$ pip install future, tox
$ pip install python-crfsuite==0.9.5
$ pip install Cython
$ pip install -U fasttext --no-cache-dir --no-deps --force-reinstall
$ pip install xgboost==0.82

Installation

$ pip install languageflow

Components

• Transformers: NumberRemover, CountVectorizer, TfidfVectorizer
• Models: SGDClassifier, XGBoostClassifier, KimCNNClassifier, FastTextClassifier, CRF

Data

Download a dataset using download command

$ languageflow download DATASET

List all dataset

$ languageflow list

Datasets

The datasets module currently contains:

• Tagged: VLSP2018-NER, VTB-CHUNK*, VLSP2016-NER*, VLSP2013-POS*, VLSP2013-WTK*
• Categorized: AIVIVN2019_SA*, VLSP2018_SA*, UTS2017_BANK, VLSP2016_SA*, VNTC
• Plaintext: VNESES, VNTQ_SMALL, VNTQ_BIG

Caution (*): With closed license dataset, you must provide URL to download

Example

Download UTS2017_BANK dataset

$ languageflow download UTS2017_BANK

Use UTS2017_BANK dataset

>>> from languageflow.data_fetcher import DataFetcher, NLPData
>>> corpus = DataFetcher.load_corpus(NLPData.UTS2017_BANK_SA)
>>> print(corpus)
CategorizedCorpus: 1780 train + 197 dev + 494 test sentences