RAG and search
Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers
Our short summary of Hugging Face’s engineering write-up. The full story, with all the detail, is on their blog.
Read the full write-up on huggingface.co (opens in a new tab)Problem
Single-vector embeddings lose detail, hurting search accuracy for specific queries.
Solution
They added a multi‑vector model that stores a vector for each token, matching queries token‑by‑token with a MaxSim operation, improving retrieval quality.
Want the architecture, code and numbers? They’re in the original post.
Read the full write-up on huggingface.co (opens in a new tab)