/QABot

Primary LanguageJupyter Notebook

QABot

Description

  • first used elastic search to build index of our database usingsquad dataset.
  • It is fast and has great advantages like it allows parallel processing.
  • It is an open-domain open-book question answering model, reader-retriever model to be more specific.
  • Retriever will take the question and search the related contexts using the external database.
  • Then reader will get the context and question from retriever and it will then returns the start and end indexes of the answer.

Reader model - deepset/bert-base-cased-squad2

Retriever model

  • Query embedding model - facebook/dpr-question_encoder-single-nq-base
  • Passage embedding model - facebook/dpr-ctx_encoder-single-nq-base

QABot