Metadata-Version: 1.2
Name: lidirl
Version: 0.0.1
Summary: LID toolkit to improve performance on spontaneous noisy text with data augmentation.
Home-page: https://github.com/rewicks/lidirl/
Author: Rachel Wicks
Author-email: rewicks@jhu.edu
Maintainer-email: rewicks@jhu.edu
License: Apache License 2.0
Description: LIDIRL is a simple toolkit for LID targeting noisy spontaneous text as one might find in internet data.It allows for training custom models or using a pretrained solution.
Keywords: language identification,lid,langid,data processing,preprocessing,NLP,natural language processing,comptuational linguistics
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Text Processing
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3
