PyTorch-BigGraph

The README explicitly states it's not optimized for graphs under 100,000 nodes and recommends other tools like KBC for better quality on small datasets.

GPU training is labeled as experimental with warnings about sharp corners and lack of documentation, making it unreliable for production use without extensive tuning.

For large graphs, users must implement custom preprocessing as the provided utility only handles small, in-memory datasets, adding significant setup overhead.

Distributed mode requires high-bandwidth networking and a shared filesystem, which may not be feasible in all environments, limiting accessibility.