  We present the IndicNLP corpus, a large-scale, general-domain corpus
containing 2.7 billion words for 10 Indian languages from two language
families. We share pre-trained word embeddings trained on these corpora. We
create news article category classification datasets for 9 languages to
evaluate the embeddings. We show that the IndicNLP embeddings significantly
outperform publicly available pre-trained embedding on multiple evaluation
tasks. We hope that the availability of the corpus will accelerate Indic NLP
research. The resources are available at
https://github.com/ai4bharat-indicnlp/indicnlp_corpus.
