dpr

Configuration and model for DPR (Dense Passage Retriever) type models.

DPR type models use two separate neural networks, known as dual encoders, to independently map a user’s question and the database of documents into a shared mathematical space. During a search, DPR finds relevant documents by measuring the distance or similarity between the single vector of the query and the vectors of the documents.

Originally proposed in Dense Passage Retrieval for Open-Domain Question Answering. This model type is also known as a SentenceTransformer model: Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Classes

DprConfig([query_length, doc_length, ...])	Configuration class for a DPR model.
DprModel(config, *args, **kwargs)	A single-vector DPR model.