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).
From the blog
Handling Unresolved Support Tickets: Escalating To Human Agents
As amazing and helpful as your ChatGPT powered custom chatbot might be, sometimes your customers or visitors still need a human touch. That's where escalating to human support comes in.
Herman Schutte
Founder
IT Help Desk Automation with SiteSpeakAI
In a world that’s constantly evolving, having a robust IT help desk is no longer a choice but a necessity for businesses. But, how can you ensure that your help desk is able to respond to queries swiftly and accurately? The answer lies in automation, and one tool that is making waves in this domain is SiteSpeakAI.
Herman Schutte
Founder