We present PyThaiNLP, a free and open-source natural language processing
(NLP) library for Thai language implemented in Python. It provides a wide range
of software, models, and datasets for Thai language. We first provide a brief
historical context of tools for Thai language prior to the development of
PyThaiNLP. We then outline the functionalities it provided as well as datasets
and pre-trained language models. We later summarize its development milestones
and discuss our experience during its development. We conclude by demonstrating
how industrial and research communities utilize PyThaiNLP in their work. The
library is freely available at this https URL

PyThaiNLP 是一个免费且开源的自然语言处理库，为泰语提供丰富的软件、模型和数据集，该文讨论了其历史背景、功能、数据集、预训练模型，发展里程碑以及在工业和研究社区中的应用。

PyThaiNLP：Python 中的泰语自然语言处理

PyThaiNLP: Thai Natural Language Processing in Python

We present mahaNLP, an open-source natural language processing (NLP) library
specifically built for the Marathi language. It aims to enhance the support for
the low-resource Indian language Marathi in the field of NLP. It is an
easy-to-use, extensible, and modular toolkit for Marathi text analysis built on
state-of-the-art MahaBERT-based transformer models. Our work holds significant
importance as other existing Indic NLP libraries provide basic Marathi
processing support and rely on older models with restricted performance. Our
toolkit stands out by offering a comprehensive array of NLP tasks, encompassing
both fundamental preprocessing tasks and advanced NLP tasks like sentiment
analysis, NER, hate speech detection, and sentence completion. This paper
focuses on an overview of the mahaNLP framework, its features, and its usage.
This work is a part of the L3Cube MahaNLP initiative, more information about it
can be found at this https URL .

mahaNLP 是一个针对马拉地语开发的开源自然语言处理（NLP）库，旨在增强 NLP 领域中对资源匮乏的印度语言马拉地的支持，它是一个易于使用、可扩展和模块化的工具包，基于最先进的 MahaBERT-based transformer 模型进行马拉地文本分析。

mahaNLP：一个马拉地文自然语言处理库

mahaNLP: A Marathi Natural Language Processing Library

We present iNLTK, an open-source NLP library consisting of pre-trained
language models and out-of-the-box support for Data Augmentation, Textual
Similarity, Sentence Embeddings, Word Embeddings, Tokenization and Text
Generation in 13 Indic Languages. By using pre-trained models from iNLTK for
text classification on publicly available datasets, we significantly outperform
previously reported results. On these datasets, we also show that by using
pre-trained models and data augmentation from iNLTK, we can achieve more than
95% of the previous best performance by using less than 10% of the training
data. iNLTK is already being widely used by the community and has 40,000+
downloads, 600+ stars and 100+ forks on GitHub. The library is available at
this https URL

介绍 iNLTK—— 这是一种开放源代码的 NLP 库，由 13 种印度语言中已经预训练好的语言模型，并提供数据增强、文本相似性、句子嵌入、词嵌入、分词和文本生成的支持。通过在公开数据集上使用 iNLTK 的预训练模型进行文本分类，我们表现优于以前的结果，并且通过在 iNLTK 中使用预训练模型和数据增强，我们可以在使用不到 10% 的训练数据的情况下达到先前最佳表现的 95% 以上。iNLTK 已广泛被社区使用，并在 GitHub 上有 40000 + 下载，600 + 星号和 100 + 叉子。