rapidsai/raft

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

CudaC++Jupyter NotebookPythonCythonCMakeOthermachine-learninginformation-retrievalstatisticsclusteringgpudistancelinear-algebracudaprimitivessparsenearest-neighborssolversvector-similarityannsrandom-samplingvector-searchbuilding-blocksllmvector-storeneighborhood-methods
This is stars and forks stats for /rapidsai/raft repository. As of 28 Apr, 2024 this repository has 382 stars and 125 forks.

 RAFT: Reusable Accelerated Functions and Tools for Vector Search and More Contents Useful Resources What is RAFT? Use cases Is RAFT right for me? Getting Started Installing RAFT Codebase structure and contents Contributing References Useful Resources RAFT Reference Documentation: API Documentation. RAFT Getting Started: Getting started with RAFT. Build and Install RAFT: Instructions for installing and building RAFT. Example Notebooks: Example jupyer notebooks RAPIDS Community: Get help, contribute,...
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