awslabs/dgl-ke
High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.
This package helps machine learning engineers or researchers working with knowledge graphs to efficiently train, evaluate, and predict using knowledge graph embeddings. It takes a knowledge graph dataset as input and produces learned embeddings, which are numerical representations of entities and relationships. These embeddings can then be used for tasks like predicting missing links or similar entities within the graph.
1,328 stars. No commits in the last 6 months.
Use this if you need to generate high-quality knowledge graph embeddings quickly and at scale, even for very large datasets.
Not ideal if you primarily need to train TransE, DistMult, or RotatE models, as GraphStorm might be a more suitable alternative for those specific models.
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1,328
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198
Language
Python
License
Apache-2.0
Category
Last pushed
Aug 08, 2025
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