  In this work, we develop language models for the Sanskrit language, namely
Bidirectional Encoder Representations from Transformers (BERT) and its
variants: A Lite BERT (ALBERT), and Robustly Optimized BERT (RoBERTa) using
Devanagari Sanskrit text corpus. Then we extracted the features for the given
text from these models. We applied the dimensional reduction and clustering
techniques on the features to generate an extractive summary for a given
Sanskrit document. Along with the extractive text summarization techniques, we
have also created and released a Sanskrit Devanagari text corpus publicly.
