answerai colbert small v1 answerai colbert small v1 is a new, proof of concept model by Answer.AI, showing the strong performance multi vector models with the new JaColBERTv2.5 training recipe and some extra tweaks can reach, even with just 33 million parameters . While being MiniLM sized, it outperforms all previous similarly sized models on common benchmarks, and even outperforms much larger popular models such as e5 large v2 or bge base en v1.5. For more information about this model or how it was trained, head over to the announcement blogpost. Usage Installation This model was designed with the upcoming RAGatouille overhaul in mind. However, it's compatible with all recent ColBERT implementations! To use it, you can either use the Stanford ColBERT library, or RAGatouille. You can install both or either by simply running. If you're interested in using this model as a re ranker (it vastly outperforms cross encoders its size!), you can do so via the rerankers library: Rerankers RAGatouille Stanford ColBERT Indexing Querying Extracting Vectors Finally, if you want to extract individula vectors, you can use the model this way: Results Against single vector models Dataset / Model ans…
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