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Knowledge Graph embedding in Python and PyTorch.

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logo torchkge https://img.shields.io/pypi/v/torchkge.svg https://travis-ci.org/torchkge-team/torchkge.svg?branch=master Documentation Status Updates

TorchKGE: Knowledge Graph embedding in Python and Pytorch.

TorchKGE is a Python module for knowledge graph (KG) embedding relying solely on Pytorch. This package provides researchers and engineers with a clean and efficient API to design and test new models. It features a KG data structure, simple model interfaces and modules for negative sampling and model evaluation. Its main strength is a highly efficient evaluation module for the link prediction task, a central application of KG embedding. It has been observed to be up to five times faster than AmpliGraph and twenty-four times faster than OpenKE. Various KG embedding models are also already implemented. Special attention has been paid to code efficiency and simplicity, documentation and API consistency. It is distributed using PyPI under BSD license.

Paper accepted at IWKG-KDD 2020. Reference coming soon.

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