no code implementations • 16 Mar 2024 • Gergely Szilvasy, Pierre-Emmanuel Mazaré, Matthijs Douze
Although convenient to compute, this metric is distantly related to the end-to-end accuracy of a full system that integrates vector search.
1 code implementation • 16 Jan 2024 • Matthijs Douze, Alexandr Guzhva, Chengqi Deng, Jeff Johnson, Gergely Szilvasy, Pierre-Emmanuel Mazaré, Maria Lomeli, Lucas Hosseini, Hervé Jégou
The Faiss library is dedicated to vector similarity search, a core functionality of vector databases.
no code implementations • 16 Oct 2023 • Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Gergely Szilvasy, Rich James, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Scott Yih, Mike Lewis
Large language models (LMs) are currently trained to predict tokens given document prefixes, enabling them to directly perform long-form generation and prompting-style tasks which can be reduced to document completion.
no code implementations • 2 Oct 2023 • Xi Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Rich James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer, Scott Yih
Retrieval-augmented language models (RALMs) improve performance by accessing long-tail and up-to-date knowledge from external data stores, but are challenging to build.