GUIDE · MODELS · #27
Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers — Hugging Face
Hugging Face published a piece about using multi-vector (late interaction) embedding models with the Sentence Transformers library. The article describes how to work with multi-vector representations and late interaction within the Sentence Transformers ecosystem for embedding-based retrieval workflows.
KEY POINTS
- Hugging Face published a piece about using multi-vector (late interaction) embedding models with the Sentence Transformers library.
- The article describes how to work with multi-vector representations and late interaction within the Sentence Transformers ecosystem for embedding-based retrieval workflows.
- Multi-vector/late-interaction methods change how similarity is computed in embedding-based retrieval, so guidance from a major ecosystem like Sentence Transformers affects practitioners building search and retrieval systems.
WHY IT MATTERS
Multi-vector/late-interaction methods change how similarity is computed in embedding-based retrieval, so guidance from a major ecosystem like Sentence Transformers affects practitioners building search and retrieval systems.