Show HN: Model2vec – Lightning-fast Static Embeddings for RAG/Semantic Search
(github.com/MinishLab)
Model2Vec is a technique to turn any sentence transformer into a really small static model, reducing model size by 15x and making the models up to 500x faster, with a small drop in performance. Our best model is the most performant static embedding model in the world. See our results here, or dive in to see how it works.
Model2Vec is a technique to turn any sentence transformer into a really small static model, reducing model size by 15x and making the models up to 500x faster, with a small drop in performance. Our best model is the most performant static embedding model in the world. See our results here, or dive in to see how it works.