Faiss
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About
Faiss is a library developed at FAIR (Facebook AI Research) for efficient similarity search and clustering of dense vectors. It supports datasets of any size, including those that don't fit in RAM, and offers algorithms implemented on GPUs for faster processing. Faiss uses various methods, including inverted files, product quantization, and hierarchical navigable small world graphs for optimized performance. It provides C++ and Python APIs for easy integration into various applications.
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Task
Features
• clustering of dense vectors
• efficient similarity search
• python and c++ apis
• gpu support
• algorithms for large datasets
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