Benchmarking Cohere Rerankers with LanceDB
Improve retrieval quality by reranking LanceDB results with Cohere and ColBERT. You’ll plug rerankers into vector, FTS, and hybrid search and compare accuracy on real datasets.
Improve retrieval quality by reranking LanceDB results with Cohere and ColBERT. You’ll plug rerankers into vector, FTS, and hybrid search and compare accuracy on real datasets.
Explore about tokens per second is not all you need. Get practical steps, examples, and best practices you can use now.
In our last blog, we talked about chunking and why it is necessary for processing data through LLMs. We covered some simple techniques to perform text chunking.
Explore lance v2: a new columnar container format with practical insights and expert guidance from the LanceDB team.
In our article, we explored the remarkable capabilities of the Lance format, a modern, columnar data storage solution designed to revolutionize the way we work with large image datasets in machine learning.
Working with large image datasets in machine learning can be challenging, often requiring significant computational resources and efficient data-handling techniques.
Explore a practical guide to fine-tuning embedding models with practical insights and expert guidance from the LanceDB team.
Streaming data applications can be tricky. When you can read data faster than you can process the data then bad things tend to happen. The various solutions to this problem are largely classified as backpressure.
Explore designing a table format for ML workloads with practical insights and expert guidance from the LanceDB team.