The crispy, lightweight ColBERT family from Mixedbread . 🍞 Looking for a simple end to end retrieval solution? Meet Mixedbread Search , our multi modal and multi lingual search solution. mxbai edge colbert v0 17m This model is a lightweight, 17 million parameter ColBERT with a projection dimension of 48. It is built on top of Ettin 17M, meaning it benefits from all of ModernBERT's architectural efficiencies. Despite this extreme efficiency, it is the best performer "edge sized" retriever, outperforming ColBERTv2 and many models with over 10 times more parameters. It can create multi vector representations for documents of up to 32,000 tokens and is fully compatible with the PyLate library. Usage To use this model, you first need to install PyLate: via uv or pip Once installed, the model is immediately ready to use to generate representations and index documents: That's all you need to do to encode a full collection! Your documents are indexed and ready to be queried: Reranking Thanks to its extreme parameter efficiency, this model is particularly well suited to being used as a re ranker following an even more lightweight first stage retrieval, such as static embeding models. Re ra…
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