The crispy sentence embedding family from Mixedbread . 🍞 Looking for a simple end to end retrieval solution? Meet Omni, our multimodal and multilingual model. Get in touch for access. mixedbread ai/mxbai embed xsmall v1 This model is an open source English embedding model developed by Mixedbread. It's built upon sentence transformers/all MiniLM L6 v2 and trained with the AnglE loss and Espresso. Read more details in our blog post. In a bread loaf : State of the art performance Supports both binary quantization and Matryoshka Representation Learning (MRL). Optimized for retrieval tasks 4096 context support Performance Binary Quantization and Matryoshka Our model supports both binary quantization and Matryoshka Representation Learning (MRL), allowing for significant efficiency gains: Binary quantization: Retains 93.9% of performance while increasing efficiency by a factor of 32 MRL: A 33% reduction in vector size still leaves 96.2% of model performance These optimizations can lead to substantial reductions in infrastructure costs for cloud computing and vector databases. Read more here. Quickstart Here are several ways to produce German sentence embeddings using our model. angle emb…
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