Getting started · facebookresearch/faiss Wiki
For the following, we assume Faiss is installed. We provide code examples in C++ and Python. The code can be run by copy/pasting it or running it from the tutorial/ subdirectory of the Faiss distribution.
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related reading
- Faiss: A library for efficient similarity search - Engineering at Metaengineering.fb.com
- GitHub - facebookresearch/faiss: A library for efficient similarity search and clustering of dense vectors.github.com
- Welcome to Faiss Documentation - Faiss documentationfaiss.ai
- GitHub - matsui528/faiss_tips: Some useful tips for faiss · GitHubgithub.com
- Indexing 1T vectors · facebookresearch/faiss Wiki · GitHubgithub.com
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- plippe/faiss-web-service - Docker Imagehub.docker.com
- Introduction to Facebook AI Similarity Search (Faiss) | Pineconepinecone.io
- Guidelines to choose an index · facebookresearch/faiss Wiki · GitHubgithub.com
- Announcing ScaNN: Efficient Vector Similarity Searchai.googleblog.com