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。