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blog.nomic.ai | ||
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zackproser.com
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| | | | | Embeddings models are the secret sauce that makes RAG work. How are THEY made? | |
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www.mixedbread.ai
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| | | | | The 2D-?? model introduces a novel approach that enables you to reduce both the number of layers and the dimensions of embeddings within the model. This dual reduction strategy allows for a more compact model size while still delivering competitive performance compared to leading models, such as Nomic's embedding model. Specifically, reducing the model's layers by approximately 50% retains up to 85% of its original performance, even without additional training. | |
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www.singlelunch.com
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| | | | | This is the blog version of a talk of mine on embedding methods. It's the main slides and what I would say in the talk. Intended audience: Anyone interested in embedding methods. I don'... | |
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blog.vespa.ai
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| | | In this post, we reproduce the state-of-the-art baseline for retrieval-based question-answering systems within a single, scalable production ready application on Vespa.ai. | ||
