Train 400x faster Static Embedding Models with Sentence Transformers
This blog post introduces a method to train static embedding models that run 100x to 400x faster on CPU than state-of-the-art embedding models, while retaining most of the quality. This unlocks a lot of exciting use cases, including on-device and in-browser execution, edge computing, low power and embedded applications.
We apply this recipe to train two extremely efficient embedding models: sentence-transformers/static-retrieval-mrl-en-v1