Try LFM • Docs • LEAP • Discord LFM2 ColBERT 350M LFM2 ColBERT 350M is a late interaction retriever with excellent multilingual performance. It allows you to store documents in one language (for example, a product description in English) and retrieve them in many languages with high accuracy. LFM2 ColBERT 350M offers best in class accuracy across different languages. Inference speed is on par with models 2.3 times smaller , thanks to the efficient LFM2 backbone. You can use it as a drop in replacement in your current RAG pipelines to improve performance. Find more information about LFM2 ColBERT 350M in our blog post. [!NOTE] 🚀 Try our demo: https://huggingface.co/spaces/LiquidAI/LFM2 ColBERT 📄 Model details Late interaction retrievers like LFM2 ColBERT 350M are particularly interesting because they preserve much of the expressivity of re rankers while retaining the efficiency of bi encoders. In practice, they're used to both retrieve documents at scale (like bi encoders) and rank them at the same time (like rerankers). We recommend using this model for various RAG use cases, such as: E commerce : Find products across many languages with semantic search at scale. On device semanti…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy