What is a Retriever Encoder?
A model component used to encode queries and documents into embeddings for retrieval tasks.
More about Retriever Encoder:
Retriever Encoder is a model responsible for converting queries and documents into vector embeddings for retrieval. These embeddings are then used in vector databases to find the most relevant information. Common encoder types include bi-encoders and cross-encoders.
The retriever encoder is central to systems like dense retrieval and semantic search, ensuring efficient and accurate information retrieval.
Frequently Asked Questions
What is the role of a retriever encoder in retrieval systems?
It encodes queries and documents into embeddings that can be compared for relevance using similarity metrics.
How does a retriever encoder differ from a generator model?
Retriever encoders fetch relevant information, while generator models create responses, often used together in retrieval-augmented generation (RAG).
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