Shypd.aiThe largest open index of AI toolsdgl-ke is a high-performance, easy-to-use, and scalable open-source package for learning large-scale knowledge graph embeddings. It supports training, evaluation, and inference tasks on various environments.
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dgl-ke is an open-source package designed for learning large-scale knowledge graph embeddings, built on top of the Deep Graph Library (DGL). It offers high performance, ease of use, and scalability, making it suitable for various machine learning tasks involving knowledge graphs. The package supports training knowledge graph embeddings using popular models like TransE, TransR, RESCAL, DistMult, ComplEx, and RotatE. Users can perform training on single machines (CPU/GPU) or distributed environments, evaluate pre-trained embeddings with link prediction tasks, and conduct inference for entity/relation linkage prediction or embedding similarity. DGL-KE is optimized for scale, capable of processing knowledge graphs with millions of nodes and billions of edges efficiently.
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