This repository would contain implementation of semantic similarity with different state of the art transformers from huggingface
Semantic similarity is used to measure the distance or similarity between two pair of words, phrases, sentences or documents. This can be done in two ways knowledge-based or corpus-based. Here we would be doing a corpus-bases approach. This implementation is inspired from semantic similarity implementation with BERT example from keras.io. The idea here is to change the models and see if we could get a better performance with other transformer architecture like t5.